organisational culture research paper

Understanding and Assessing Organizational Culture

• First Online: 03 January 2022

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• Sonja A. Sackmann   ORCID: orcid.org/0000-0001-7846-652X 2  

Part of the book series: Contributions to Management Science ((MANAGEMENT SC.))

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Chapter 7 addresses the topic of culture assessment. A culture assessment entails gaining knowledge about an organization’s culture by analyzing it and its evaluation. First, the chapter outlines those characteristics of organizational culture relevant to its analysis because analysts’ conception of culture and its characteristics influence the approach they choose for a culture analysis, including methods. Second, the chapter explores different kinds of data collection methods, including their strengths and related challenges, for collecting information about an organization’s culture. Third, the chapter addresses standards helpful in evaluating the quality of a given culture, and it provides two examples of a culture assessment in practice.

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Sackmann, S.A. (2021). Understanding and Assessing Organizational Culture. In: Culture in Organizations. Contributions to Management Science. Springer, Cham. https://doi.org/10.1007/978-3-030-86080-6_7

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• v.2; Jan-Dec 2021

Measures of organizational culture, organizational climate, and implementation climate in behavioral health: A systematic review

Byron j powell.

1 Brown School and School of Medicine, Washington University in St. Louis, St. Louis, MO, USA

Kayne D Mettert

2 Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA

Caitlin N Dorsey

Bryan j weiner.

3 Department of Global Health and Department of Health Services, University of Washington, Seattle, WA, USA

Cameo F Stanick

4 Hathaway-Sycamores Child and Family Services, Pasadena, CA, USA

Rebecca Lengnick-Hall

Mark g ehrhart.

5 Department of Psychology, University of Central Florida, Orlando, FL, USA

Gregory A Aarons

6 Department of Psychiatry, School of Medicine, University of California San Diego, La Jolla, CA, USA

Melanie A Barwick

7 Hospital for Sick Children, Toronto, ON, Canada

Laura J Damschroder

8 Ann Arbor VA Center for Clinical Management Research, Ann Arbor, MI, USA

Cara C Lewis

Associated data.

Supplemental material, sj-pdf-1-irp-10.1177_26334895211018862 for Measures of organizational culture, organizational climate, and implementation climate in behavioral health: A systematic review by Byron J Powell, Kayne D Mettert, Caitlin N Dorsey, Bryan J Weiner, Cameo F Stanick, Rebecca Lengnick-Hall, Mark G Ehrhart, Gregory A Aarons, Melanie A Barwick, Laura J Damschroder and Cara C Lewis in Implementation Research and Practice

Background:

Organizational culture, organizational climate, and implementation climate are key organizational constructs that influence the implementation of evidence-based practices. However, there has been little systematic investigation of the availability of psychometrically strong measures that can be used to assess these constructs in behavioral health. This systematic review identified and assessed the psychometric properties of measures of organizational culture, organizational climate, implementation climate, and related subconstructs as defined by the Consolidated Framework for Implementation Research (CFIR) and Ehrhart and colleagues.

Data collection involved search string generation, title and abstract screening, full-text review, construct assignment, and citation searches for all known empirical uses. Data relevant to nine psychometric criteria from the Psychometric and Pragmatic Evidence Rating Scale (PAPERS) were extracted: internal consistency, convergent validity, discriminant validity, known-groups validity, predictive validity, concurrent validity, structural validity, responsiveness, and norms. Extracted data for each criterion were rated on a scale from −1 (“poor”) to 4 (“excellent”), and each measure was assigned a total score (highest possible score = 36) that formed the basis for head-to-head comparisons of measures for each focal construct.

We identified full measures or relevant subscales of broader measures for organizational culture ( n  = 21), organizational climate ( n  = 36), implementation climate ( n  = 2), tension for change ( n  = 2), compatibility ( n  = 6), relative priority ( n  = 2), organizational incentives and rewards ( n  = 3), goals and feedback ( n  = 3), and learning climate ( n  = 2). Psychometric evidence was most frequently available for internal consistency and norms. Information about other psychometric properties was less available. Median ratings for psychometric properties across categories of measures ranged from “poor” to “good.” There was limited evidence of responsiveness or predictive validity.

Conclusion:

While several promising measures were identified, the overall state of measurement related to these constructs is poor. To enhance understanding of how these constructs influence implementation research and practice, measures that are sensitive to change and predictive of key implementation and clinical outcomes are required. There is a need for further testing of the most promising measures, and ample opportunity to develop additional psychometrically strong measures of these important constructs.

Plain Language Summary

Organizational culture, organizational climate, and implementation climate can play a critical role in facilitating or impeding the successful implementation and sustainment of evidence-based practices. Advancing our understanding of how these contextual factors independently or collectively influence implementation and clinical outcomes requires measures that are reliable and valid. Previous systematic reviews identified measures of organizational factors that influence implementation, but none focused explicitly on behavioral health; focused solely on organizational culture, organizational climate, and implementation climate; or assessed the evidence base of all known uses of a measure within a given area, such as behavioral health–focused implementation efforts. The purpose of this study was to identify and assess the psychometric properties of measures of organizational culture, organizational climate, implementation climate, and related subconstructs that have been used in behavioral health-focused implementation research. We identified 21 measures of organizational culture, 36 measures of organizational climate, 2 measures of implementation climate, 2 measures of tension for change, 6 measures of compatibility, 2 measures of relative priority, 3 measures of organizational incentives and rewards, 3 measures of goals and feedback, and 2 measures of learning climate. Some promising measures were identified; however, the overall state of measurement across these constructs is poor. This review highlights specific areas for improvement and suggests the need to rigorously evaluate existing measures and develop new measures.

Introduction

Because most behavioral health services are delivered within or through organizations ( Aarons et al., 2018 ), organizational context plays a critical role in determining successful implementation of evidence-based practices (EBPs; Aarons et al., 2014 , 2018 ; Glisson & Williams, 2015 ). Consequently, organizational context is included in ~95% of implementation frameworks ( Tabak et al., 2012 ). The purpose of this systematic review was to identify and assess the psychometric properties of measures of organizational culture, organizational climate, and implementation climate used in behavioral health-related implementation studies. We drew upon conceptualizations of these constructs and related subconstructs from the Consolidated Framework for Implementation Research (CFIR; Damschroder et al., 2009 ) and from the book by Ehrhart, Schneider, et al. (2014) (see Table 1 ).

Construct definitions.

Note . Definitions from all constructs aside from organizational climate are drawn from Additional File 3 of Damschroder et al. (2009) . The definition of organizational climate is taken from Ehrhart, Schneider, et al. (2014) .

Organizational culture

Organizational culture is defined as “. . . the shared values and basic assumptions that explain why organizations do what they do and focus on what they focus on” ( Schneider et al., 2017 , p. 468). There are debates regarding its definition and measurement ( Aarons et al., 2018 ; Ehrhart, Schneider, et al., 2014 ; Kimberly & Cook, 2008 ; Schein, 2017 ; Verbeke et al., 1998 ). Verbeke and colleagues (1998) identified 54 definitions of organizational culture, and Aarons and colleagues (2018) described six different measures that use 3–10 different dimensions each to measure culture (e.g., involvement, adaptability, mission, attention to detail, aggressiveness, innovation, supportiveness, leadership, planning, communication, hierarchy, proficiency, and apathy), with very little overlap. In behavioral health, organizational culture has been empirically linked to attitudes toward EBPs, sustainment, access to services, service quality, staff turnover, and mental health outcomes ( Glisson & Williams, 2015 ).

Organizational climate

Organizational climate is defined as “the shared meaning organizational members attach to the events, policies, practices, and procedures they experience and the behaviors they see being rewarded, supported, and expected” ( Ehrhart, Schneider, et al., 2014 , p. 69). Scholars differentiate molar organizational climate from focused climates. Molar conceptualizations refer to the extent to which leadership provides positive experiences for employees ( Aarons et al., 2018 ) and can include dimensions such as engagement, functionality, and stress ( Glisson et al., 2008 ). In behavioral health, molar organizational climate has been empirically linked to service quality, treatment planning decisions, attitudes toward EBPs, staff turnover, and mental health outcomes ( Glisson & Williams, 2015 ). Others have conceptualized and measured focused aspects of climate, such as an outcome (e.g., climate for safety) or organizational process (e.g., ethics, fairness) ( Aarons et al., 2018 ).

Implementation climate

Implementation climate is a type of focused organizational climate defined as a summary of employees’ shared perceptions of the extent to which their use of an innovation is rewarded, supported, and expected ( Klein & Sorra, 1996 ). Strong implementation climates encourage use of EBPs by (1) ensuring employees are skilled in their use, (2) incentivizing the use of EBP and eliminating disincentives, and (3) removing barriers to EBP use ( Klein & Sorra, 1996 ). Implementation climate differs from molar organizational climate in that it is innovation-specific and focuses on organizational members who are expected to use or directly support an innovation ( Weiner et al., 2011 ). Implementation climate may be critical to improving EBP implementation ( Williams et al., 2018 , 2020 ). Williams and colleagues’ (2020) 5-year panel analysis showed that organizations that improved from low to high levels of implementation climate had significantly greater increases in their clinicians’ average EBP use.

Previous reviews

Reviews of the organizational culture and organizational climate measures vary along several dimensions. First, some have systematically reviewed the literature (e.g., Allen et al., 2017 ; Chaudoir et al., 2013 ; Clinton-McHarg et al., 2016 ), whereas others have selectively reviewed measures at the discretion of the authors (e.g., Glisson & Williams, 2015 ; Kimberly & Cook, 2008 ; Schneider et al., 2013 ). Second, they range from narrow (e.g., organizational culture only; Jung et al., 2009 ; King & Byers, 2007 ; Scott et al., 2003 ) to broad assessments (e.g., a list of organizational characteristics; Allen et al., 2017 ; Brennan et al., 2012 ; Chaudoir et al., 2013 ). Third, they may or may not report psychometric properties and/or report them with varying degrees of granularity (e.g., Schneider et al., 2013 , and Kimberly & Cook, 2008 , do not report psychometric properties; Chaudoir et al., 2013 , focused on criterion validity). Finally, they may (e.g., Clinton-McHarg et al., 2016 ) or may not (e.g., Gershon et al., 2004 ; Jung et al., 2009 ) be informed by a conceptual framework.

Two published systematic reviews examined psychometric properties of measures for constructs within the “inner setting” domain of the CFIR ( Damschroder et al., 2009 ). Clinton-McHarg and colleagues (2016) examined quantitative measures developed for public health and community settings and located 51 measures. Most did not report on psychometric properties and those that did typically fell below accepted standards ( Clinton-McHarg et al., 2016 ). Allen et al. (2017) identified 83 measures of the inner setting and the two constructs with the most measures were readiness for implementation and organizational climate. However, only 46% of studies ( n  = 35) included information about psychometric properties, and of those, 94% (33/35) described reliability and 71% (25/35) reported validity.

Aims and contribution of the current study

The current study sought to identify and assess the psychometric properties of measures of organizational culture, organizational climate, and implementation climate used in behavioral health-related implementation studies. This review contributes to the implementation and behavioral health literatures by (1) focusing explicitly on the assessment of these constructs within behavioral health; (2) identifying measures for key constructs and subconstructs of the widely used CFIR ( Damschroder et al., 2009 ); and (3) rigorously assessing evidence of measures’ psychometric strength by using the Psychometric and Pragmatic Evidence Rating Scale (PAPERS; Lewis, Mettert, et al., 2018 ; Stanick et al., 2021 ). Our intent is to inform researchers’, EBP purveyors’ ( Proctor et al., 2019 ), implementation support practitioners’ ( Albers et al., 2020 ), and other stakeholders’ selection of high-quality measures, and to highlight areas in which further development and testing of measures is necessary.

Design overview

Data for this systematic review come from a project funded by the U.S. National Institute of Mental Health, which included multiple systematic reviews that identified implementation determinant ( Damschroder et al., 2009 ) and outcome ( Proctor et al., 2011 ) measures that were used within implementation studies in behavioral health ( Lewis et al., 2018 ). The protocol for that study has been published elsewhere ( Lewis et al., 2018 ). This systematic review was conducted in three phases. Phase I, data collection, included five steps: (1) search string generation, (2) title and abstract screening, (3) full text review, (4) construct assignment, and (5) measure-forward searches. Phase II, data extraction, consisted of coding relevant psychometric data, and Phase III involved data analysis.

Phase I: data collection

Literature searches were conducted in PubMed and Embase using search strings curated in consultation from PubMed support specialists and a library scientist. PubMed and Embase are commonly recommended for systematic reviews in health ( Bramer et al., 2017 ; Higgins et al., 2021 ). Other databases such as PsycINFO were considered, but pilot testing revealed that search yields were low and did not identify a substantial number of studies for the constructs of interest. Search terms focused on: (1) implementation; (2) measurement; (3) EBP; (4) behavioral health; and (5) organizational culture and implementation climate. Our conceptualization of organizational culture and implementation climate was guided by the CFIR ( Damschroder et al., 2009 ), and included search terms for organizational culture, implementation climate, and related subconstructs: tension for change, compatibility, relative priority, organizational incentives and rewards, goals and feedback, and learning climate (see Table 1 ). Table 2 includes a complete listing of search terms for PubMed and Embase. Articles published in English from 1985 onwards were included in the search. Searches were completed from 3 April 2017 to 25 May 2017.

Database search terms.

Identified titles and abstracts were screened, followed by full-text review to confirm relevance to study parameters. We included empirical studies that contained one or more quantitative measures of the target constructs if they were used in an evaluation of an implementation effort in a behavioral health context. See Table 3 for inclusion/exclusion criteria, and Appendix 1 for PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) flowcharts ( Figures 10 to ​ to17 17 ).

Inclusion and exclusion criteria.

The next step involved construct assignment, in which trained research specialists mapped measures and/or their subscales to the target constructs based on the authors’ conceptualization of the measure and content expert coding. Inherent to our search approach, measures of the target constructs could be identified through systematic reviews of related constructs (e.g., organizational readiness for change) conducted in the parent study ( Lewis et al., 2018 ). For example, a subscale from Organizational Readiness for Change Assessment (“Staff Culture”) by Helfrich et al. (2009) was identified in a review of measures of organizational readiness for change ( Weiner et al., 2020 ). The CFIR does not include molar organizational climate; thus, we did not conduct a search specifically for that construct. However, our searches for organizational culture and implementation climate identified a number of measures of molar organizational climate. We attempted to maintain a conceptual distinction between measures of molar organizational climate or focused organizational climates (e.g., risk taking climate; Cook et al., 2012 ) and the more intervention-specific implementation climate construct as described by Weiner et al. (2011) . Thus, we ultimately categorized measures into nine different constructs: organizational culture, organizational climate, implementation climate, tension for change, compatibility, relative priority, organizational incentives and rewards, goals and feedback, and learning climate ( Table 1 ).

Finally, “measure-forward” searches were conducted in May 2019 for each measure to identify empirical articles that used the measure in behavioral health implementation research. These searches were conducted using the “cited-by” feature in PubMed and Embase and by searching for measures’ formal names as available.

Phase II: data extraction

Next, articles were compiled into “measure packets,” including the measure itself (as available), the measure development article (or article with the first empirical use in a behavioral health context), and all identified empirical uses of the measure in behavioral health-related implementation efforts. Trained-research specialists reviewed each article and electronically extracted information relevant to nine psychometric rating criteria from the PAPERS ( Lewis, Mettert, et al., 2018 ; Stanick et al., 2021 ): (1) internal consistency, (2) convergent validity, (3) discriminant validity, (4) known-groups validity, (5) predictive validity, (6) concurrent validity, (7) structural validity, (8) responsiveness, and (9) norms ( Table 4 ). Data were collected on both full measure and subscale levels. If a full measure was relevant to a target construct, we reported psychometric evidence for the full measure. However, if only subscales of a broader measure were relevant, we reported psychometric evidence at the subscale level. We use the term “measures” throughout this article to refer to both full measures and subscales; however, the distinction between the two is maintained by using formal names of measures and subscales in relevant tables and figures.

Definitions of psychometric properties.

Note . See Additional File 2 of Lewis, Mettert, et al. (2018) for the complete rating scale for each psychometric criterion.

After PAPERS relevant data were extracted ( Lewis, Mettert, et al., 2018 ; Stanick et al., 2021 ), each criterion was rated using the following scale for which nuanced anchors established: “poor” (−1), “none” (0), “minimal/emerging” (1), “adequate” (2), “good” (3), or “excellent” (4 ) . Ratings were summarized using a “rolled up median” approach in an effort to assign a single score for each criterion. This is more reflective of the range of measure performance than often used “top score” or “worst score counts” methods ( Lewis et al., 2015 ; Terwee et al., 2012 ). If a measure was unidimensional or the measure had only one rating for a criterion, then this value was the final rating. If a measure had multiple ratings for a criterion across several articles, we calculated the median score to generate the final rating. For example, if a measure was used in five different studies, each of which included evidence of internal consistency, we calculated the median to determine that measures’ final rating of internal consistency. If the computed median resulted in a non-integer rating, the non-integer was rounded down (e.g., internal consistency ratings of 2 and 3 would result in a 2.5 median, which was rounded down to a 2). In cases where the median of two scores would equal “0” (e.g., a score of −1 and 1), the lower would be taken (e.g., −1). This approach results in a conservative rating.

In addition to assessing psychometric properties, we extracted: (1) whether the measure was used more than once, (2) country of origin, (3) setting (e.g., inpatient psychiatry, outpatient), (4) level of analysis (e.g., consumer, organization, provider), (5) population (e.g., general mental health, anxiety, depression), and (6) stage of implementation as defined by the exploration, adoption/preparation, implementation, sustainment model ( Aarons et al., 2011 ).

Phase III: data analysis

Simple statistics (frequencies, medians, ranges) were calculated to report on the presence and quality of psychometric data. Each measure was assigned a total score based upon the nine PAPERS criteria (highest possible score = 36). Bar charts were generated to display head-to-head comparisons across all measures within a given construct.

Table 5 provides descriptive information. Table 6 shows availability of psychometric evidence. Table 7 includes the median and range of ratings of psychometric properties for measures with psychometric information available (i.e., those with non-zero ratings on the PAPERS criteria; Lewis, Mettert, et al., 2018 ; Stanick et al., 2021 ). Individual ratings for all measures are detailed in Table 8 and in head-to-head bar graphs in Figures 1 to ​ to9 9 .

Description of measures and subscales.

Psychometric information availability.

Summary statistics for instrument ratings.

Note . Scores for individual measures ranged from −1 (“poor”) to 4 (“excellent”). Median, excluding zeros where psychometric information was not available. When the median of two scores would equal “0” (e.g., a score of −1 and 1), the lower score was taken.

Psychometric ratings for each measure by focal construct.

Head-to-head comparison of measures of organizational culture.

Head-to-head comparison of measures of learning climate.

Head-to-head comparison of measures of organizational climate.

Head-to-head comparison of measures of implementation climate.

Head-to-head comparison of measures of tension for change.

Head-to-head comparison of measures of compatibility.

Head-to-head comparison of measures of relative priority.

Head-to-head comparison of measures of organizational incentives and rewards.

Head-to-head comparison of measures of goals and feedback.

We identified 21 measures of organizational culture, 18 of which are subscales of broader measures (e.g., Organizational Readiness for Change Assessment–Staff Culture Scale; Helfrich et al., 2009 ). Measures were primarily developed in the United States (95%); used more than once (76%); used most frequently in outpatient community mental health (86%) and residential care settings (71%); administered most frequently at the provider (100%) or supervisor (52%) levels; used within general mental health (86%), alcohol use (57%), or substance use disorder (67%) services; and were used most frequently at the exploration (71%) and implementation (43%) phases.

Evidence of internal consistency was available for 18 measures, convergent validity for two measures, known-groups validity for two measures, predictive validity for 12 measures, concurrent validity for two measures, structural validity for one measure, responsiveness for one measure, and norms for 20 measures. No psychometric evidence was available for discriminant validity.

The median rating for internal consistency was “2—adequate,” for convergent validity “2—adequate,” for known-groups validity “−1—poor,” for predictive validity “1—minimal,” for concurrent validity “−1—poor,” for structural validity “2—adequate,” and for norms “2—adequate.” The median rating of “2—adequate” for structural validity was based on the rating of just one measure: the Organizational Social Context–Culture Scale ( Glisson et al., 2008 ).

The most frequently used and highest rated measure of organizational culture in behavioral health (with 46 uses of culture and/or climate scales) was the Organizational Social Context–Culture Scale ( Glisson et al., 2008 ). It received a total score of 11 (maximum possible score = 36) and had evidence of internal consistency (“3—good”), convergent validity (“1—minimal”), predictive validity (“1—minimal”), concurrent validity (“2—adequate”), structural validity (“2—adequate”), responsiveness (“2—adequate”), and norms (“1—minimal”), along with a “−1—poor” rating for known-groups validity. The next highest scoring measure of organizational culture was the Organizational Description Questionnaire ( Parry & Proctor-Thomson, 2001 ) that was used eight times (total score = 9; maximum possible score = 36), with ratings of “2—adequate” for internal consistency, “3—good” for convergent validity, and “4—excellent” for norms.”

We identified 36 measures of organizational climate, 32 of which are subscales of broader measures (e.g., Survey of Organizational Functioning–Organizational Climate Domain; Broome et al., 2007 ). Measures were primarily developed in the United States (94%); used more than once (75%); used most frequently in outpatient community mental health (92%) and residential care settings (47%); administered at the provider (78%), director (67%), supervisor (64%), and clinic/site levels (61%); used within substance use disorder (72%) and general mental health services (50%); and were used most often at the implementation (64%) and exploration phases (53%).

Evidence for internal consistency was available for 31 measures, convergent validity for five measures, discriminant validity for one measure, known-groups validity for 13 measures, predictive validity for 19 measures, concurrent validity for two measures, structural validity for five measures, responsiveness for three measures, and norms for 35 measures.

The median rating for internal consistency was “3—good,” for convergent validity “3— good ,” for discriminant validity “−1—poor,” for known-groups validity “2—adequate,” for predictive validity “1—minimal,” for concurrent validity “1—minimal,” for structural validity “2—adequate,” for responsiveness “1—minimal,” and for norms “2—adequate.” The median rating of “−1—poor” for discriminant validity was based upon one measure: the Organizational Climate Measure ( Patterson et al., 2005 ).

The measure that scored the highest (total score = 13; maximum possible score = 36) among the organizational climate measures was the Texas Christian University Program Training Needs Survey ( Simpson, 2002 ), which was used five times and showed evidence of internal consistency (“2—adequate”), known-groups validity (3—good”), predictive validity (“2—adequate”), structural validity (“2—adequate”), and norms (“4—excellent”). The Organizational Social Context—Climate ( Glisson et al., 2008 ), the most frequently used measure in behavioral health received a total score of 12 (maximum possible score = 36). This included evidence of internal consistency (“3—good”), known-groups validity (“1—minimal”), predictive validity (“2—adequate”), concurrent validity (“1—minimal”), structural validity (“2—adequate”), responsiveness (“1—minimal”), and norms (“2—adequate”). Finally, few measures used in behavioral health focus solely on organizational climate. One exception is the Organizational Climate Measure ( Patterson et al., 2005 ). It had been used twice in behavioral health, had a total score of 9 (maximum possible score = 36), and had evidence of internal consistency (“2—adequate”), discriminant validity (“−1—poor”), predictive validity (“2—adequate”), concurrent validity (“1—minimal”), structural validity (“1—minimal”), and norms (“4—excellent”).

For implementation climate, we included measures directly addressing implementation climate or measures of any of the six subconstructs that the CFIR includes as contributing to a positive implementation climate, including tension for change, compatibility, relative priority, organizational incentives and rewards, goals and feedback, and learning climate. We refer readers to Table 5 for descriptive information.

We identified two measures of implementation climate, one of which is a subscale of a broader measure (Readiness for Integrated Care Questionnaire–Implementation Climate Scale; Scott et al., 2017 ).

Of two measures of implementation climate, evidence of norms was available for both and evidence of internal consistency, convergent validity, discriminant validity, predictive validity, structural validity, and norms was available for one measure. Neither measure had evidence for known-groups validity, concurrent validity, or responsiveness.

The Implementation Climate Scale ( Ehrhart, Aarons, et al., 2014 ) had the highest overall rating (total score = 11; maximum possible score = 36) from five uses in behavioral health, demonstrating evidence of internal consistency (“3—good”), convergent validity (“2—adequate”), discriminant validity (“1—minimal”), predictive validity (“1—minimal”), structural validity (“2—adequate”), and norms (“2—adequate”).

Tension for change

We identified two measures of tension for change, both of which were subscales of broader measures (e.g., Texas Christian University Organizational Readiness for Change–Pressures for Change Scale; Lehman et al., 2002 ). Evidence of internal consistency and norms was available for both measures, and evidence of convergent validity, known-groups validity, and predictive validity was available for one measure. There was no evidence of discriminant validity, concurrent validity, structural validity, or responsiveness. Both measures were rated the same (total score = 3; maximum possible score = 36). The Texas Christian University Organizational Readiness for Change–Pressures for Change Subscale ( Lehman et al., 2002 ) demonstrated evidence of internal consistency (“2—adequate”), convergent validity (“1—minimal”), and norms (“2—adequate”); however, both known-groups validity and predictive validity were rated as (“−1—poor”) despite being used 37 times in behavioral health. The Survey of Organizational Functioning–Pressures for Change Subscale ( Broome et al., 2007 ) was used 12 times and exhibited evidence of internal consistency (“1—minimal”) and norms (“2—adequate”).

Compatibility

We identified six measures of compatibility, all of which were subscales of broader measures (Perceived Characteristics of Intervention Scale–Compatibility Scale; Cook et al., 2015 ). Evidence of internal consistency was available for three measures, evidence of predictive validity was available for one measure, and evidence of norms was available for two measures. There was no evidence for convergent validity, discriminant validity, known-groups validity, concurrent validity, structural validity, or responsiveness. The highest rated measure was the Perceived Characteristics of Intervention Scale–Compatibility Subscale ( Cook et al., 2015 ), which had been used twice and received a total score of five (maximum possible score = 36) and demonstrated evidence of internal consistency (“3—good”) and norms (“2—adequate”). The next highest rated measure was the Cook Implementation Measure–Compatibility Scale ( Cook et al., 2012 ), which had been used four times and showed evidence of internal consistency (“3—good”) and predictive validity (“1—minimal”).

Relative priority

We identified two measures of relative priority, both of which are subscales of broader measures (e.g., Cook Implementation Measure–Goals and Priorities; Cook et al., 2012 ). Evidence of internal consistency was available for one measure and evidence of norms was available for one measure. There was no information available on any of the remaining psychometric criteria. The highest rated measure was the Cook Implementation Measure–Goals and Priorities ( Cook et al., 2012 ), which had been used four times and a total score of three (maximum possible score = 36) based upon evidence of internal consistency (“3—good”).

Organizational incentives and rewards

We identified three measures of organizational incentives and rewards, all of which were subscales of broader measures (e.g., Implementation Climate Scale–Rewards Scale; Ehrhart, Aarons, et al., 2014 . Evidence of internal consistency was available for all three measures, and evidence of predictive validity and norms was available for one measure. No further information about psychometric properties was available. The Implementation Climate Scale–Rewards Subscale ( Ehrhart, Aarons, et al., 2014 ) was used five times and received the highest overall rating (total score = 5; maximum possible score = 36), demonstrating evidence of internal consistency (“2—adequate”), predictive validity (“1—minimal”), and norms (“2—adequate”).

Goals and feedback

We identified three measures of goals and feedback, all of which were subsets of broader measures (e.g., Chou Measure of Guideline Information–Feedback Scale; Chou et al., 2011 ). Evidence for internal consistency was available for two measures, and evidence of convergent validity, predictive validity, and norms was available for one measure. No other information on psychometric properties was available. The Organizational Readiness for Change Assessment–Project Progress Tracking Subscale ( Helfrich et al., 2009 ; four uses in behavioral health) was rated the highest (total score = 4; maximum possible score = 36), with evidence of internal consistency (“3—good”) and norms (“1—minimal”). The Cook Implementation Measure–Goals and Priorities Subscale ( Cook et al., 2012 ) received a total score of three, with evidence of internal consistency (“3— good ”).

Learning climate

We identified two measures of learning climate, one of which was a subscale from a broader measure (The National Criminal Justice Treatment Practices Survey–Climate for Learning Scale; Taxman et al., 2007 ). Evidence of norms was available for two measures and evidence for internal consistency, convergent validity, predictive validity, and concurrent validity were available for one measure. There was no evidence of discriminant validity, known-groups validity, structural validity, or responsiveness. The Ramsey Learning Climate Measure ( Ramsey et al., 2015 ) was rated the highest (total score = 6; maximum possible score = 36), with evidence of internal consistency (“4—excellent”), convergent validity (“−1—poor”), concurrent validity (“1—minimal”), and norms (“2—adequate”).

Summary of findings

This systematic review of measures of organizational culture, organizational climate, implementation climate, and related constructs in behavioral health identified some promising measures; however, consistent with other reviews of organizational constructs ( Allen et al., 2017 ; Clinton-McHarg et al., 2016 ; Weiner et al., 2020 ), the overall state of measurement across these constructs is poor. While 21 measures of organizational culture and 36 measures of organizational climate were identified, the vast majority were subscales within broader measures. Far fewer measures of implementation climate and related constructs were identified. Previous work has documented the problem of “home-grown” measures that are used only once ( Lewis et al., 2015 ; Martinez et al., 2014 ). Encouragingly, more than 75% of measures of organizational culture and organizational climate identified in this review were used more than once, which may reflect the long tradition of these constructs in the broader literature ( Ehrhart, Schneider, et al., 2014 ). In contrast, nearly half of the measures of implementation climate and related subconstructs were used only once, perhaps reflecting its more recent emergence in the field ( Klein & Sorra, 1996 ; Weiner et al., 2011 ).

Limited psychometric evidence was available for the identified measures of organizational culture, organizational climate, implementation climate, and its subconstructs. This is consistent with findings from previous reviews of a broader set of implementation constructs ( Chaudoir et al., 2013 ; Clinton-McHarg et al., 2016 ), as well as findings from a recent review of organizational readiness for change ( Weiner et al., 2020 ). For organizational culture and organizational climate, evidence of internal consistency and norms was available for most measures. Evidence of predictive validity was available for over half of identified measures, though nine of them received a rating of “poor” suggesting that evidence did not support study hypotheses. Evidence for other psychometric properties like known-groups validity, concurrent validity, convergent validity, discriminant validity, structural validity, and responsiveness was sparse. Generally, psychometric evidence for implementation climate and its related subconstructs was less readily available. Only one measure of organizational culture ( Glisson et al., 2008 ), five measures of organizational climate ( Anderson & West, 1998 ; Broome et al., 2007 ; Glisson et al., 2008 ; Patterson et al., 2005 ; Simpson, 2002 ), and one measure of implementation climate ( Ehrhart, Aarons, et al., 2014 ) were assessed for structural validity, which is concerning given that a measure’s dimensionality should be checked prior to checking its internal consistency ( DeVellis, 2012 ). Also concerning is a striking lack of evidence for measure responsiveness (i.e., sensitivity to change), as only four measures among all focal constructs possessed evidence of responsiveness ( Chodosh et al., 2015 ; Glisson et al., 2008 ; Lehman et al., 2002 ). This weakness will stymie efforts to identify organizational-level mechanisms that explain how and why implementation strategies can improve implementation and clinical outcomes ( Lewis et al., 2020 ; Lewis, Klasnja, et al., 2018 ; Williams, 2016 ; Williams et al., 2017 ).

Overall measurement quality was found to be poor. With the exception of internal consistency, most median ratings ranged from “−1—poor” to “2—adequate.” Only seven measures received an overall score of 10 or higher (out of a possible score of 36) on the PAPERS psychometric rating criteria ( Lewis, Mettert, et al., 2018 ; Stanick et al., 2021 ). The Organizational Social Context measures of culture and climate received scores of 11 and 12, respectively, and represent the most frequently studied measure in behavioral health-focused implementation research with national norms established in mental health ( Glisson et al., 2008 ) and child welfare ( Glisson et al., 2012 ). An additional four measures were in the organizational climate domain, including the Texas Christian University Program Training Needs Survey (total score = 13; Simpson, 2002 ) and three subscales from the Texas Christian University Organizational Readiness for Change measure (“Mission,” “Cohesion,” and “Stress”; Lehman et al., 2002 ) that total scores of 12, 11, and 11. The Texas Christian University Program Training Needs Survey ( Simpson, 2002 ) has only been used five times in behavioral health, but with ratings of “2—adequate” to “4—excellent” on five different psychometric criteria, it may have promise for further use and evaluation. While the Texas Christian University Organizational Readiness for Change measure ( Lehman et al., 2002 ) scored relatively high in comparison to other measures included in this review, there was no evidence of structural validity or responsiveness, and only “minimal” evidence of predictive validity despite 37 uses in behavioral health, suggesting that more uses may not offer more positive psychometric evidence. The last measure to receive a score of 10 or higher was the Implementation Climate Scale (total score = 11; Ehrhart, Aarons, et al., 2014 ), which has been used five times in behavioral health. Given its promising psychometric properties and desirable pragmatic properties (free, only 18 items), this scale demonstrates promise.

Future directions

There is a need to prioritize further psychometric evaluation of promising measures that have yet been used frequently in behavioral health. There are also opportunities to rigorously develop new measures of sparsely populated constructs, particularly for the subconstructs of measures of implementation climate.

Though we did not explicitly consider the extent to which identified measures are pragmatic ( Powell et al., 2017 ; Stanick et al., 2018 , 2021 ), it will be critical to do so moving forward. Some measures identified in this review are brief and freely available, while others are quite long and proprietary. Measures’ pragmatic properties are likely to influence their use in both research and applied implementation efforts.

Organizational culture and implementation climate are broad constructs that have been conceptualized and measured in a wide range of ways ( Aarons et al., 2018 ; Ehrhart, Schneider, et al., 2014 ; Kimberly & Cook, 2008 ; Schneider et al., 2013 ; Verbeke et al., 1998 ). It would be useful to pursue conceptual and measurement work to delineate ways in which organizational culture and organizational climate have been measured. This work could guide stakeholders wanting to measure specific aspects of organizational culture and organizational climate and illustrate the trade-offs in prioritizing one conceptualization versus another. An additional opportunity may be to develop more holistic profiles of organizational culture and climate using latent profile analysis ( Glisson et al., 2014 ; Williams et al., 2019 ). For example, Williams et al. (2019) demonstrated that when individual dimensions of culture and climate or the linear combination of all six dimensions were not predictive of fidelity to an EBP, a “comprehensive” profile (high proficiency culture, positive climate) was predictive of fidelity for two of three EBPs. This demonstrates that culture and climate may interact in complex ways, and that “the overall gestalt of the social context may be more important than the level of a single dimension” ( Williams et al., 2019 , p. 10).

Given calls for improved reporting in implementation research ( Wilson et al., 2017 ), it may be useful to develop reporting guidelines for measurement in implementation studies. These may differ depending upon the type of study. For example, a measure development study may require different minimum criteria as compared to the use of a measure within a broader implementation study.

Limitations

This study has several limitations. First, as with all systematic reviews, it is possible that we failed to identify articles that could have detailed measures of the focal constructs or provided further data on their psychometric evidence. There are at least four potential reasons for this: (1) we did not search explicitly for molar organizational climate since that construct is not included in the CFIR, which was used to generate our search strategy for organizational culture, implementation climate, and related constructs; (2) we did not search the gray literature; (3) the original literature searches for this study were completed in 2017; and (4) we did not search all potentially relevant databases (e.g., PsycINFO, Google Scholar; Bramer et al., 2017 ). Additional measures of the focal constructs may have been published since the original search date; however, we captured more recent uses of the measures we identified in 2017 by conducting measure-forward “cited-by” searches in May of 2019. Nevertheless, there are also studies that provide additional evidence for included measures that have been published since our measure-forward search (e.g., Beidas et al., 2019 ; Williams et al., 2020 ). One measure of implementation climate developed by Jacobs et al. (2014) was not identified in this review (likely because initial development in testing was in both non-behavioral health and behavioral health settings), but appears to have promising psychometric and pragmatic properties. Second, there are inevitable measures of the focal constructs developed outside of behavioral health, and some of the measures identified in this review may have evidence of further use outside of implementation efforts in behavioral health service settings. Thus, it is important that readers interpret these ratings within this context rather than as an indicator of the measures’ overall quality or psychometric strength. Third, it is possible that our assignment of measures and/or subscales to the nine focal constructs was imperfect, particularly given the substantial overlap between the conceptualization and measurement of organizational culture, organizational climate, and related constructs ( Kimberly & Cook, 2008 ). Finally, it is possible that poor reporting practices limit the extent to which evidence was available for identified measures (i.e., it is possible that more thorough evaluations of psychometric properties were conducted but not reported).

This systematic review identifies measures of organizational culture, organizational climate, and implementation climate used in behavioral health-focused implementation studies. Several promising measures were identified, and can inform researchers, EBP purveyors, implementation support practitioners, and others who wish to measure these constructs. However, to enhance understanding of how these constructs influence EBP implementation, there is a need for further testing of the most promising approaches, development of additional psychometrically and pragmatically strong measures, and approaches that elucidate the ways in which “dimensions of organizational culture and climate interact with, reinforce, and counteract one another in complex, non-linear ways as they relate to EBP implementation . . .” ( Williams et al., 2019 , p. 10).

Supplemental Material

PRISMA diagram for organizational culture.

Note that the number of articles identified did not equal the number of measures included in the analysis because in some cases a single measure was identified in multiple articles, and in others, multiple measures were identified in a single article.

PRISMA diagram for implementation climate.

PRISMA diagram for tension for change.

PRISMA diagram for compatibility.

PRISMA diagram for relative priority.

PRISMA diagram for organizational incentives and rewards.

PRISMA diagram for goals and feedback.

PRISMA diagram for learning climate.

The author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: Funding for this study came from the National Institute of Mental Health, awarded to Dr Cara C. Lewis as principal investigator. Dr Lewis is an author of this article and editor of the journal, Implementation Research and Practice . Due to this conflict, Dr Lewis was not involved in the editorial or review process for this article.

Funding: The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the National Institute of Mental Health (NIMH) through R01MH106510 (Lewis, PI). Byron Powell was also supported by the NIMH through K01MH113806 (Powell, PI).

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Organizational culture Organizational culture is embedded in the everyday working lives of all cultural members. Manifestations of cultures in organizations include formal practices (such as pay levels, structure of the HIERARCHY,JOB DESCRIPTIONS, and other written policies); informal practices (such as behavioral norms); the organizational stories employees tell to explain “how things are done around here;” RITUALS (such as Christmas parties and retirement dinners); humor (jokes about work and fellow employees); jargon (the special language of organizational initiates); and physical arrangements (including interior decor, dress norms, and architecture). Cultural manifestations also include values, sometimes referred to more abstractly as content themes. It is essential to distinguish values/content themes that are espoused by employees from values/content themes that are seen to be enacted in behavior. All of these cultural manifestations are interpreted, evaluated, and enacted in varying ways because cultural members have differing interests, experiences, responsibilities and values.

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Organizational culture, innovation and performance: a study from a non-western context

Journal of Management Development

ISSN : 0262-1711

Article publication date: 13 January 2020

Issue publication date: 13 October 2020

The purpose of this paper is to examine the links between organizational culture, innovation and banks’ performance in Palestine.

Design/methodology/approach

Data were gathered from 186 employees working in the Palestinian banking sector. The data gathered were analyzed using the PLS-SEM approach.

The findings of the study show that organizational culture and marketing innovation have a positive impact on banks’ performance. Moreover, it was found that marketing performance partially mediates the relationship between organizational culture and banks’ performance.

Practical implications

The paper may be of use for banks managers to create an organizational culture, which fosters both innovation and performance.

Originality/value

The paper is unique as it examines organizational culture, innovation and performance links in a non-western context.

• Performance
• Technological innovation

Organizational culture

• Marketing innovation

Aboramadan, M. , Albashiti, B. , Alharazin, H. and Zaidoune, S. (2020), "Organizational culture, innovation and performance: a study from a non-western context", Journal of Management Development , Vol. 39 No. 4, pp. 437-451. https://doi.org/10.1108/JMD-06-2019-0253

Emerald Publishing Limited

Copyright © 2020, Mohammed Aboramadan, Belal Albashiti, Hatem Alharazin and Souhaila Zaidoune

Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode

Introduction

Nowadays, organizations need to operate in business environments, which are characterized by fast technological changes, intensive international competition and continuous changing client’s preferences ( Droge et al. , 2008 ). Given these complexities, innovation is seen as one of the critical factors for achieving organizational success and sustaining competitive advantage ( Damanpour and Gopalakrishnan, 2001 ). It is well documented in the literature that innovative organizations have more flexibility and can respond quickly to changes, in order to take advantage of business opportunities ( Drucker, 1985 ). Innovation is considered as a competitive mechanism for organizations’ performance and success, and is regarded as an important instrument to adapt to a continuously changing business environment ( Blackwell, 2006 ). Furthermore, previous studies provide evidence that innovation can positively affect performance (e.g. Baker and Sinkula, 2002 ; Damanpour and Gopalakrishnan, 2001 ; Luk et al. , 2008 ; Naranjo-Valencia et al. , 2016 ; Uzkurt et al. , 2013 ).

Because of the critical role innovation plays in different organizational settings, several scholars have attempted to determine the factors that are associated with influencing innovation ( Koc and Ceylan, 2007 ). One of the factors that seems to have an impact on innovation is the organizational culture ( Büschgens et al. , 2013 ; Lin et al. , 2013 ; Martins and Terblanche, 2003 ; Tushman and O’Reilly, 1997 ).

On the other hand, organizational culture has been studied in terms of definitions, theoretical scopes, conceptualizations, characteristics and types (e.g. Lavine, 2014 ; Schein, 1996 ). Although organizational culture was argued to contribute to achieving common values promotion ( Naranjo-Valencia et al. , 2016 ), competitive advantage ( Calciolari et al. , 2018 ) desirables employees’ behaviors ( Nazarian et al. , 2017 ; Zhang and Li, 2016 ) and innovation ( Lin et al. , 2013 ), empirical support is still limited ( Hartnell et al. , 2011 ; Kim and Chang, 2019 ).

Regardless of the important role organizational culture plays in promoting innovation, most of the studies were carried out in western contexts. Moreover, a very limited number of studies examined the association between organizational culture and performance through the intervening mechanisms such as innovation (e.g. Martins and Terblanche, 2003 ; Naranjo-Valencia et al. , 2016 ; Uzkurt et al. , 2013 ).

Our study contributes to the literature in several ways. First, we attempt to investigate the “black box” of the organizational culture-performance relationship through the mediating effects of marketing and technology innovation. Based on a critical review of previous empirical studies, very limited research (e.g. Naranjo-Valencia et al. , 2016 ; Tseng et al. , 2008 ; Uzkurt et al. , 2013 ) examined the role of innovation as a mediator between organizational culture and performance. Second, our study responds to the different scholarly calls to advance empirical research on innovation and organizational culture ( McLaughlin et al. , 2008 ; Nakata and DiBenedetto, 2012 ; Tellis et al. , 2009 ). Finally, most of the studies examining organizational culture and performance were carried out in western setting. For instance, Budhwar et al. (2019) suggested that there is a need to enrich the literature of HRM and organizational behavior research in the Middle Eastern region. Among the suggestions made by Budhwar et al. (2019) was to investigate the mechanisms which govern the relationship between OB, HR factors and organizational performance. Given this discussion and to respond the scholarly calls to advance the organizational behavior and HR research in the Middle East, our study aims at investigating the relationship between organizational culture and banks performance via the mediating role of innovation. Moreover, we argue that more studies are needed in diverse non-western settings, in order to better understand the relationship between organizational culture and performance.

Theory and hypotheses

Organizational culture, definitions and models.

Chang and Lin (2007) consider culture as one of the vital factors for organizations and their activities. In literature, many definitions were given to organizational culture, each from a different perspective. Overall, organizational culture commonly represents the routine activities taking place in an organization ( Lundy and Cowling, 1996 ). More specifically, it refers to the shared set of values and behaviors inside an organization ( Deshpande and Webster, 1989 ). It is also used to describe the set of assumptions and behaviors employees within an organization have adopted ( Martins and Terblanche, 2003 ). Many researchers were interested in the field of organizational culture assuming it is a driving factor to the organization’s innovation, productivity and financial performance ( Blackwell, 2006 ).

Many studies were conducted to determine the different categories of organizational culture ( Blackwell, 2006 ; Martins and Terblanche, 2003 ). Some of them have considered that organizational culture can be divided into four categories, namely, clan, hierarchy, adhocracy and market ( Cameron and Freeman, 1991 ; Deshpande et al. , 1993 ; Quinn, 1988 ). Quinn and Spreitzer (1991) have suggested that organizational culture is composed of four different cultures: development culture, group culture, rational culture and hierarchal culture. Similarly, Chang and Lin (2007) believe that organizational culture follows the four concepts of: innovativeness, cooperativeness, effectiveness and consistency. In addition, Wallach (1983) suggested a simpler classification of the organizational culture following its functions: bureaucratic, innovative and supportive perspectives. A further classification for the culture was presented in the organizational culture profile suggesting that it is related to seven main values: innovation, aggressiveness, result orientation, stability, people orientation, team oriented and a detail focus culture. The organization’s culture can be also classified according to being a: service culture organization that focuses on providing the highest value to its customers, or a safety culture that focuses on having strong work-place standards, or both ( O’Reilly III et al. , 1991 ). Moreover, according to Robbins (2001) , characteristics like leadership, risk aversion, amount of detail, result focus, people focus, team focus, hostility and stability are the main characteristics of organizational culture.

Organizational culture and performance

Organizational culture has a significant impact on banks’ performance.

Innovation, on the other hand, is used to refer to new products, services, processes or technologies that require acceptance and eventually adoption and implementation ( Damanpour, 1991 ; Thompson, 1965 ; Zaltman et al. , 1973 ). Innovation is the factor that enables the innovative processes to produce new products and services, new technologies and new concepts ( Sutanto, 2017 ).

According to Padilla-Meléndez and Garrido-Moreno (2012) , knowledge of innovation needs more communication, and interaction between not only researchers, but also stakeholders affected by this, as well as, leaders. This way new ideas, processes and interactions can have an economic and commercial benefit. Hence, leaders, managers and researchers in organizations and universities should be aware of the different ways of innovation.

Innovation, in the literature, can be divided into different types. The most popular typology of innovation divides it into three types: “administrative vs technical,” “product vs process” and “radical vs incremental” ( Gopalakrishnan and Damanpour, 1997 ). Another classification of the typologies of innovation was developed by Jensen et al. (2007) . According to this classification, innovation can be classified as: “Science, Technology and Innovation” (STI) that is based on analytical knowledge and “Doing, Using, and Interaction” that is subject to knowledge retrieved from the engineering field ( Coenen and Asheim, 2006 ; Lorenz and Lundvall, 2006 ). Innovation can be divided into three groups: product-related, technology-related and behavior-related perspectives. The technology-related innovation is related to the readiness to adopt current technologies and processes and the tendency of the organization to adopt new technologies and processes internally ( Kitchell, 1995 ). Behavior-related innovation relates to the speed, at which the organizational system is ready to adopt new ideas relative to competitors ( Rogers, 1995 ). Lastly, product-related innovation is about the ability of an organization to generate new ideas, products, services and processes, or to buy them ( Stalk et al. , 1992 ). Moreover, as innovation is responsible for implementing totally new or ameliorated versions of products, services or processes within the organization, or in the external relations ( OECD and EUROSTAT, 2005 ), innovation can be classified into four categories. First, product innovation, which refers to the radical changes or ameliorations done to products and services. Second, process innovation, which refers to the major changes done to the production system or to the delivery mode. Third, organizational innovation, which refers to the adoption of new business processes that affect the business process within the organization and or on external relations. And fourth, marketing innovation, which refers to any change made to one of the four marketing Ps (product, price, placement and position) ( OECD and EUROSTAT, 2005 ).

Organizational culture and innovation

As innovation plays a significant role in determining an organization’s success, several studies attempted to examine its antecedences ( Crossan and Apaydin, 2010 ). Different studies found that organizational culture and organizational design are the most influential determinants ( Mumford, 2000 ).

Organizational culture can affect the innovative attitude in two ways. The socialization process teaches individuals how to behave and act toward one another. Moreover, the organization’s structure, policy system, procedure and management orientation can be affected by the basic “values, beliefs and assumptions” ( Martins and Terblanche, 2003 ). Hence, culture can encourage innovation among employees, because it drives them toward accepting innovation as a philosophy of the organization ( Hartmann, 2006 ). Different values of culture were regarded as means to foster innovation. Examples of these cultural values were creativity and initiative ( Jamrog et al. , 2006 ), entrepreneurial mindset ( McLean, 2005 ), freedom and autonomy ( Ahmed, 1998 ), risk taking ( Wallach, 1983 ), teamwork ( Arad et al. , 1997 ), marketing orientation and flexibility ( Martins and Terblanche, 2003 ).

Organizational culture has a significant impact on marketing innovation.

Organizational culture has a significant impact on technology innovation.

Innovation and performance

Research has found that innovation plays a significant role in organization performance ( Higgins, 1995 ; Hult et al. , 2004 ). Organizations able to innovate are more capable to deliver new products and services, improve processes in a faster way to fit the market’s needs and capitalize on opportunities better than non-innovative organizations ( Jiménez-Jiménez et al. , 2008 ). Moreover, innovation has been associated with higher levels of growth and profitability ( Li and Atuahene-Gima, 2001 ).

Marketing innovation has a significant impact on banks performance.

Technology innovation has a significant impact on banks performance.

The present study is a quantitative study applied to the Palestinian banking sector with the purpose of examining the hypothesized positive relationships between organizational culture, marketing innovation, technological innovation and banks’ performance. Data were gathered using a self-administered questionnaire distributed to the employees of banking sector located in Gaza strip. The distribution and collection method were the drop-off and pick up approach. A total of 320 employees were invited to fill the questionnaire. A total of 186 filled and usable questionnaires were gathered and valid for statistical analysis. The response rate in our study is 58 percent.

Respondents’ profile

Most of the respondents were male (70 percent). In total, 25.8 percent of the respondents were aged higher than 44 years, 25.8 percent were aged less than 30 years, 38.7 percent were aged from 30 to 38 years and 9.7 percent were aged from 38 to 44 years. Regarding experience, 32.3 percent had 5–10 years of experience, 16.1 percent had 10–15 years of experience, 22.6 percent had an experience of more than 15 years and 29 percent had less than 5 years of experience. Concerning education, most of the respondents had a bachelor’s degree (87.1 percent).

This scale is measured using 22 items adopted from previous studies, such as Claver et al. (1998) , Denison and Mishra (1995) , Jamrog et al. (2006) , McLean (2005) and Wallach (1983) . These items were “teamwork, communication, openness, work autonomy, commitment, employee’s involvement, flexibility, creativity, responsibility, objective orientation, customer focus, continuous learning, risk taking, adaptability, entrepreneurial mindset, performance incentives, excitement, work engagement, decision making, marketing orientation, and high standards and values.” The internal consistency was 0.956. A five-point Likert scale was used to assess the items of this construct.

Marketing and technology innovation

Marketing innovation and technological innovation were measured by a three-item scale for each. Both scales were adopted from Hogan et al. (2011) . A sample item for marketing innovation is “Our bank develops, revolutionary for the industry, marketing programs for our services/products” and a sample item for technology innovation is “Our bank adopts the latest technology in the industry.” The values of international consistency for marketing and technological innovation were 0.848 and 0.765, respectively. A five-point Likert scale was used to assess the items of these two constructs.

Banks’ performance

Respondents assessed this measure using a seven-item scale adopted from Agbényiga (2011) . Examples of this self-reported assessment were “effective services, customer satisfaction, organizational reputation, quality of the service.” The internal consistency value was 0.921. A five-point Likert scale was used to assess the items of this construct.

Initial analysis

Table I shows correlations and descriptive statistics of the research variables. The means and SDs for the examined variables were (Mean: 4.15, SD: 0.55) for organizational culture, (Mean: 4.44, SD: 0.48) for marketing innovation, (Mean: 4.56, SD: 0.45) for technology innovation, and (Mean: 4.30, SD: 0.60) for banks’ performance. According to the results, correlations were significant between marketing innovation, organizational culture and performance.

Assessing the measurement model

For the purpose of checking the internal consistency of the items, factor loading was calculated for each variable. Three items of organizational culture were removed from the model due to their low loading. All other items loadings were retained as their factor loading was higher than 0.5 as presented in Figure 1 . Furthermore, we have checked for the variables’ reliability by calculating the average variance extracted and composite reliability ( Hulland, 1999 ). As presented in Table II , AVE values for all variables were higher than 0.5 and CR values were higher than 0.7 ( Hulland, 1999 ). Hence, all variables in the model can be regarded as internally reliable and consistent.

For the purpose of examining discriminant validity, two approaches were utilized. First, the heterotrait–monotrait (HTMT) method was used, in which the results ( Table III ) show that HTMT values are lower than the value of 0.90, as suggested by Henseler et al. (2015) . The second method was the Fornell and Larcker (1981) technique by estimating the square root of the AVE and comparing it with the correlations between latent variables. The results in Table IV show that all square roots of the AVE are higher than the correlations between the examined variables. Hence, the discriminant validity condition was met.

Assessing the structural model

Table V shows that the R 2 values for banks’ performance and marketing innovation exceed the acceptable moderate ratio as suggested by Chin (1998) . Banks performance has an R 2 value of 0.561, marketing innovation an R 2 value of 0.112. Technological innovation had a week value of R 2 of 0.055. On the other hand, the effect size f ² for the research variables was also calculated. Results of f ² values presented in Table VI showed medium effects for the following relationships: organizational culture on performance, organizational culture on marketing innovation and marketing innovation on performance. On the contrary, the effect was week for the technological innovation and performance link.

Testing the hypotheses: direct and mediating effects

For the purpose of testing the research hypotheses H1 – H5 , we have calculated the direct effects. Table VII shows all the hypotheses were supported expect for H5 . Organizational culture is positively related to banks’ performance ( β =0.596, p =0.000). Organizational culture is positively related to both marketing innovation ( β =0.334, p =0.000) and technology innovation and ( β =0.234, p =0.000). Marketing innovation was found to exert a positive effect on performance ( β =0.297, p =0.000). The relationship between technology innovation and performance was not significant ( β =−0.001, p =0.982).

For the purpose of testing the mediating effects of both marketing and technology innovation, we have calculated the indirect effects. The results show that marketing innovation mediates the relationship between organizational culture and banks performance ( P =0.007, t =2.698***). Technology innovation did not exert a significant mediating effect between organizational culture and performance.

Discussion and implications

The purpose of our study was to examine the links between organizational culture, innovation and banks’ performance in a non-western context (Palestinian context). The findings of our study provide evidence for the relationship between organizational culture and banks performance, supporting H1 . The results of our study are in line with previous studies demonstrating a positive relationship between organizational culture and performance (e.g. Daft, 2007 ; Fey and Denison, 2003 ; Kim and Chang, 2019 ; Kraśnicka et al. , 2018 ; Ngo and Loi, 2008 ; Salimi and Aveh, 2016 ). The results imply that the values and philosophy adopted within Palestinian banks contribute positively to the banks performance.

Concerning the relationship between organizational culture and innovation, our results show that organizational culture is a significant predictor of both marketing and technology innovation at Palestinian banks, lending a support for H2 and H3 . The results are consistent with previous studies, which investigate organizational culture-innovation links ( Büschgens et al. , 2013 ; Chang and Lee, 2007 ; Lau and Ngo, 2004 ; Lin et al. , 2013 ; Miron et al. , 2004 ; Naranjo-Valencia et al. , 2016 ; Rezaei et al. , 2018 ; Tseng et al. , 2008 ; Uzkurt et al. , 2013 ). The results imply that organizational culture fosters both marketing and technology innovation.

Although our results provide empirical evidence on the links between marketing innovation and banks’ performance ( H4 ) and are in line with previous empirical support ( Afcha, 2011 ; Artz et al. , 2010 ; Baker and Sinkula, 2002 ; Damanpour, 1991 ; Farley et al. , 2008 ; Luk et al. , 2008 ; Tseng et al. , 2008 ), technology innovation did not exert any significant effect on banks performance, lending no support for H5 . These results can be justified by the fact that in a developing country like Palestine, technology-related innovation might not attract customers, due to the lack of culture and trust in using different technologies (ATM machines, online banking, etc.). This means that innovating at the technological level does not necessarily contribute to higher performance in the Palestinian banking sector.

Finally, our results show that marketing innovation plays an intervening role in the relationship between organizational culture and banks performance. Marketing innovation partially mediates this relationship, suggesting that organizational culture affects marketing innovation and marketing innovation, in turn, generates higher performance.

Implications

Our results contribute both to the theory and practice. Theoretically, the study is one of the very few studies conducted in a non-western context in the banking sector. In Middle Eastern region and specifically in Palestine, there is a lack of research on the culture-innovation-performance relationships.

Practically, our results provide useful recommendations to banks’ senior management on the significance of organizational culture and innovation and their contribution to performance. Our findings provide fertile grounds for the banking sector in Palestine on the importance of organizational culture as a tool for encouraging innovation and banks performance. The presence of a strong culture that is characterized by teamwork, communication, openness, work autonomy, commitment, employee’s involvement, flexibility, creativity, responsibility, etc., will positively contribute to innovation and firm performance alike. The existence of a climate that is characterized by objective orientation, customer focus, continuous learning, risk taking, adaptability, entrepreneurial mindset, performance incentives, excitement, work engagement, decision making, marketing orientation, and high standards and values, is of extreme importance to the firm success at different levels. Moreover, the results provide insights to the banking sector which is striving to be responsive to challenging environments through successfully adopting innovation.

The Palestinian banking sector encountered several environmental complexities in the last years, hence, innovation can be very useful in order to sustain competitive advantage. Managers in Palestinian banks should encourage their staff members to create innovative ideas and provide them the right reward to establish an innovative culture in the organization. Furthermore, communication between banks’ employees at the horizontal and vertical level can be very beneficial to find the best ways to implement innovation at different levels.

Limitations and future research

Like any other study, our study has some limitations. First, marketing innovation, technology innovation and banks’ performance were assessed by subjective measures. Future research might consider using more objective measures of innovation. Second, data were collected only from the Palestinian banking sector and this might restrict the generalizability of the results to other sectors. Hence, future research might replicate and extend this study to other sectors in Palestine and similar national contexts in the region such as Jordan and Lebanon. Future research using larger data and across different sectors will give more insights on the association between organizational culture and performance through innovation. Third, our research design does not allow the researchers to establish cause and effect links between the examined variables, hence, longitudinal research is recommended for future devours. In general, organizational culture research conducted using only quantities techniques provide restricted understanding. Hence, future studies might consider using qualitative methods to provide better explanation of the organizational culture, innovation and performance associations. Finally, our research analyzed only the role of marketing and technology innovation in the banking sector. Future studies might consider examining the role of other forms of innovation. Finally, it would be also interesting for future studies to investigate the different types of organizational culture and their impact on innovation and performance in the Middle Eastern region.

PLS measurement model analysis

Means, standard deviation and correlation matrix