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The Role of Organizational Culture and Decision Making in Achieving Organizational
Innovative Capability and Performance: The Moderating Role of Allocentrism
Dr. MEHMET KIZILOGLU
1, Dr. MOHAMMED ALI YOUSEF YAMIN
21Pamukkale University,Management and Organization Department,Kinikli Campus, Turkey 2University of Jeddah,Human Resources Management,Jeddah, Saudi Arabia
1[email protected],2[email protected]
Article History: Received: 10 January 2021; Revised: 12 February 2021; Accepted: 27 March 2021; Published
online: 28 April 2021
Abstract: This study strives to investigate factor influence on organization innovative capability and performance
with an integrated research model underlying factors such as organizational culture, decision making and allocentrism. For research design, researcher has opted quantitative research approach under positivist paradigm. Sample size is computed with prior-power analysis. Using convenience sampling approach 299 valid responses were retrieved. Data were analyzed with latest statistical approach namely structural equation modeling (SEM). Results indicate that newly developed research model has substantial variance (𝑅2 79.7%) in organizational
innovative capability. Theoretically, findings of this study enrich organizational culture and decision making style literature. Practically, this research suggests that policy makers should focus on factors like allocentrism, culture adaptability and culture consistency in order to enhance performance.
Keywords: Organizational innovative capability; Organizational culture; Decision making style; Allocentrism;
Structural equation modeling
1 Introduction
Achieving organizational innovative capability is crucial due to volatile and uncertain business environment. Innovation brings prosperity and sustainability in business operations which in turn increase organization performance (Botelho, 2020; Tian & Zhai, 2019). In academic literature, there is a consensus that innovation has multiple facets and may exist in product, process, service or culture (Boon, Den Hartog, & Lepak, 2019; Botelho, 2020). In human resource context, authors like Botelho (2020) has confirmed significant impact of organizational culture and human resource practices in achieving organizational innovative capability. Another study conducted by Lasrado and kassem (2020) emphasized on organizational culture to achieve business excellence. Therefore, little has been discussed on decision making style and organizational innovative capability (Tian & Zhai, 2019). The current research fills the research gap and develop an integrative research model that encompasses essential dimensions of organizational culture and decision making style to better understand how these factors augment organizational innovative capability and organizational performance.
Organizational culture is studied by Lasrado and kassem (2020) and Gabel-Shemueli, Westman, Chen, and Bahamonde (2019) to investigate business excellence and employee work engagement. Therefore, the current research underpinned Denison culture model D. R. Denison and Mishra (1995) to investigate organizational innovative capability which is in line with Botelho (2020). There are four dimensions that are outlined in current research model including culture adaptability, culture mission, culture involvement and culture consistency (D. R. Denison & Mishra, 1995). Concerning with decision making style research took help from literature Abubakar, Elrehail, Alatailat, and Elçi (2019); Driver and Rowe (1979); Krasniqi, Berisha, and Pula (2019); Salo and Allwood Carl (2011); Verma, Bhat Aruna, Rangnekar, and Barua (2015) and synthesized decision making styles into four dimension namely rational, intuitive, dependent and spontaneous decision styles. Author like Gabel-Shemueli et al. (2019) posited that collective efforts are required to achieve competitive organizational goals. Following that, the moderating role of allocentrism is tested between the relationship of organizational innovative capability and organizational performance. The current research is significant as it combines decision making styles, cultural dimensions, and employee allocentrism characteristics altogether into one research model and examine organizational innovative capability phenomena.
2 Literature review
2.1 Organizational culture
There are strong evidences that organizational culture is directly related to business excellence and organizational performance (D. R. Denison & Mishra, 1995; Lasrado & kassem, 2020; Para-González, Jiménez-Jiménez, & Martínez-Lorente Angel, 2018). In human resource literature, organizational culture is defined as “the
core values, belief, and principles that an organization use in designing management practices which in turn enrich organizational performance” (D. Denison, Nieminen, & Kotrba, 2014; D. R. Denison & Mishra, 1995). There are
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different models that examine organizational culture nevertheless, Denison culture model has been identified as the most reliable cultural model (D. R. Denison & Mishra, 1995). The Denison model has four components including culture adaptability, culture mission, culture involvement and culture consistency (D. R. Denison & Mishra, 1995). The term adaptability in culture is defined as organizational ability to perceive and respond internal and external environment, organizational learning to modify customers behaviors. Culture adaptability has shown significant impact in innovative capability (Lasrado & kassem, 2020). Culture mission is defined as the extent wherein organizations have clear vision and goals (D. R. Denison & Mishra, 1995). Literature in organizational culture has shown strong support for culture mission and innovative capability (Botelho, 2020; D. Denison et al., 2014; D. R. Denison & Mishra, 1995). Thus, following above arguments and supported by earlier studies Botelho (2020); Boyce, Nieminen, Gillespie, Ryan, and Denison (2015); D. Denison et al. (2014); Lasrado and kassem (2020), culture adaptability and culture mission are hypothesized as:H1: Culture adaptability has positive influence in innovative capability. H2: Culture mission has positive influence in innovative capability.
The involvement kind of culture is referred to employee inclusion or participation in designing business strategies (Botelho, 2020; D. R. Denison & Mishra, 1995). Literature has confirmed positive impact of culture involvement in achieving business excellence and employee innovative capabilities Botelho (2020); Boyce et al. (2015); D. Denison et al. (2014); Lasrado and kassem (2020). Therefore, culture consistency is referred to conformity and consensus among employees. Consistency attributes are included agreement, integration, and coordination among employees to achieve business performance (Botelho, 2020). It is argued that organization that followed consistent culture have more committed employees. Moreover, under consistence culture employees get clear instruction which in turn augment organization performance. A recent study conducted by Botelho (2020) has confirmed that culture consistency and culture involvement positively influence in employee innovation capability. Therefore, and supporting by previous studies conducted by Botelho (2020); Boyce et al. (2015); D. Denison et al. (2014); Lasrado and kassem (2020), following hypotheses are proposed:
H3: Culture involvement has positive influence in innovative capability. H4: Culture consistency has positive influence in innovative capability.
2.2 Decision making styles
The concept of decision making is explained as the degree in which individual displays learned and habitual response to make a decision (Scott & Bruce, 1995). Authors like Driver and Rowe (1979) have defined decision making style as the extent wherein individual use learned and habitual response while confronting decision making situation. Extending to this, Scott and Bruce (1995) have classified decision making style into five categories including intuitive, spontaneous, dependent, avoidant and rational decision making styles. The intuitive decision making style reflects towards reliable feelings and hunches. Therefore, rational decision making style is based on logical evaluation and thorough information. The dependent decision making style is characterized by other’s directions and advices. Moving further, the avoidant decision making style directs to avoid decisions making. Therefore, the spontaneous decision making style is referred to quick and immediate decisions. According to Appelt, Milch, Handgraaf, and Weber (2011) decision making style vary according to situation. However, it remains unchanged in psychological and cognitive decision styles. Earlier studies have confirmed that intuitive and rational decision making significantly influence on organizational innovative capability and organizational performance (Abubakar et al., 2019; Renecle, Gracia, Tomas, & Peiró, 2020; Verma et al., 2015). Therefore, we hypothesized:
H5: Rational decision style has positive impact in employee innovative capability. H6: Intuitive decision style has positive influence in employee innovative capability.
The importance of dependent decision style and spontaneous decision style is inspected in previous studies Abubakar et al. (2019); Appelt et al. (2011); Verma et al. (2015). According to Abubakar et al. (2019) organizations performance is directly linked to managerial decisions that how they respond to the situation. Another study conducted by Verma et al. (2015) transformational leaders have more characteristics of dependent decision making style. The reason lie in the fact that, the transformational leader stimulates other to act as a leader and take their opinions in decisions (Verma et al., 2015). Similarly, Michailidis and Banks (2016) argued that right decision making reduce employee burnout and increase productivity. Concerning with spontaneous decision style authors like Salo and Allwood Carl (2011) postulated that quick response to a decision reduce delay in business operations and increase organizational productivity. Therefore, the current study assumes that spontaneous decision style and dependent decision style enhance innovative capability of the employees which is supported by earlier studies Driver and Rowe (1979); Krasniqi et al. (2019); Salo and Allwood Carl (2011). Thus, dependent, and spontaneous decision style are hypothesized as:
H7: Dependent decision style has positive influence in employee innovative capability. H8: Spontaneous decision style has positive influence in employee innovative capability
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2.3 The moderating role of allocentrism
The concept of allocentrism is referred to individual orientation that how they behave, feel, act and control the situation in a society or at workplace (Gabel-Shemueli et al., 2019). Allocentrism is defined as a situation in which individual give importance to harmony, shows belongingness and subservience towards group or organization. More precisely employees with allocentric characteristics give priority to achieve collective organizational goals instead of achieving individual goals. In literature allocentric and idiocentric terminologies have been discussed collectively. Therefore, the current study is focused on allocentric characteristics of an employee to achieve organizational performance. Earlier studies have recognized that allocentrism is not only discussed to interpret organization environment, but it has been found as moderating variable between employee job characteristics and organizational outcomes (Aktaş, 2014; Gabel-Shemueli et al., 2019; Nahum-Shani & Somech, 2011). Author like Aktaş (2014) has confirmed moderating role of allocentrism between job fit and job attitude. Another study conducted by Gabel-Shemueli et al. (2019) revealed that employee with allocentric characteristics have been identified source of inspiration for other team members. Similarly, Nahum-Shani and Somech (2011) explains that allocentrism boost employee trust and bring innovation in organization. Thus, allocentrism is hypothesized as:
H9: The innovative capability has positive influence organizational performance.
H10: The moderating relationship between innovative capability and organizational performance will be stronger when allocentrism is higher.
Fig-1: Theoretical framework
3 Research methods 3.1 Scale development
To test the research model, a research questionnaire is developed. Previously developed scales were adopted and then adapted into current research setting. Scale items for constructs intuitive decision style, dependent decision style, rational decision style and spontaneous decision style were adopted from Scott and Bruce (1995). Scale items for innovative capability were adopted from Chowhan (2016) and (Matthew, 2014). Therefore, scale items for culture adaptability, culture consistency, culture involvement and culture mission were adopted from D. R. Denison and Mishra (1995) and Kotrba et al. (2012). Construct items for allocentrism were adopted from Dorfman and Howell (1988). Organizational performance items were adopted from Abubakar et al. (2019). For empirical analysis scale items were measured with seven-point Likert scale exhibiting strongly disagree (1) to strongly agree (7) in line with earlier studies Samar Rahi and Abd. Ghani (2018) and Hair, Anderson, Black, and Babin (2016).
3.2 Sample size and data collection
The research design of this study is based on positivism paradigm. For sample size researcher took help from prior-power analysis as suggested by Samar Rahi (2017). According to Samar Rahi (2017) prior-power analysis provides an adequate sample size by considering exogenous indicators and appropriate for factor analysis. Result of the prior-power analysis revealed that with 10 indicators a sample of 294 respondents is sufficient for factor analysis. For data collection an administrative survey was conducted towards managers of well-established organizations in Saudi Arabia. As this study investigates decision making style thus, managers were the most
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suitable respondents. Using convenience sampling approach 350 questionnaires were delivered among employees. Convenience sampling approach was used since list of the managers was not accessible. This method is also supported by earlier studies Mohammad Ali Yamin and Swaiess (2019) and Samar; Rahi, Khan, and Alghizzawi (2020). Among 350 questionnaires, 310 returned with a response rate of 88%, indicating substantial response rate. During initial screening 11 questionnaires were discarded due to inappropriate filling in line with earlier studies Samar Rahi, Abd.Ghani, and Hafaz Ngah (2019); M. Yamin (2020). Finally, 299 responses were used for structural equation modeling (SEM).
3.3 Testing common method variance issue
According to Samar Rahi, Ghani, and Ngah (2020) postulated that common method variance issue may arise if data is collected at one point of time against all endogenous and exogenous variables. Therefore, testing common method variance issue is essential before inferential analysis. In this study, researcher has followed statistical and procedural remedies in order to avoid common method variance issue in line with Podsakoff, MacKenzie, Lee, and Podsakoff (2003). In procedural remedies all questionnaires were jumbled up as suggested by Podsakoff et al. (2003). Therefore, within statistical remedies Harman factor analysis is incorporated. Result of the Harman factor analysis had shown that the variance explained by first factor was only 27% and less than threshold value 40% (Podsakoff et al., 2003). These findings confirmed that data is free from common method variance issue and valid for inferential analysis.
4 Data analysis
To analyze the relationship between hypothesis, structural equation modeling approach is applied following guidelines provided by S. Rahi (2017). According to S. Rahi (2017) structural equation modeling approach is the latest statistical approach that allows researcher to evaluate multiple variable in a single model. For structural equation modeling, we followed two-stage approach as in line with Anderson and Gerbing (1988) and Samar Rahi, Othman Mansour Majeed, Alghizzawi, and Alnaser Feras (2019). The measurement model confirms construct validity and reliability therefore, structural model estimates structural path between two hypotheses. The detail of these two stages is given in following sections.
4.1 Measurement model
The measurement model estimates construct reliability, validity, indicator reliability and convergent validity of the constructs. Constructs reliability and validity is tested with composite reliability and alpha (α) following criterion that the values of alpha (α) and composite reliability must be higher than 0.70, in line with Samar Rahi, Abd.Ghani, et al. (2019). Therefore, indicator reliability is achieved following standard that the values of loading should be higher than 0.60 Samar Rahi and Abd. Ghani (2019a). Similarly, the convergent validity of the construct is achieved following criterion that the values of average variance extracted should be higher than 0.50 indicating adequate convergent validity of the construct (Rahi Samar & Abd Ghani Mazuri, 2019). Table 1 exhibits the results of measurement model.
Table 1 - Assessing measurement model
Scale Items Loadin
gs Alph a CR AVE Allocentrism
ALC1: For me group welfare is essential instead of individual reward.
0.816 0.798 0.882 0.7 13 ALC2: At work place my preference is to maintain harmony
within my group.
0.834
ALC3: I give priority to bring uniqueness within my group instead of individual uniqueness.
0.882
Culture adaptability
CLA1: My organization has potential to create change. 0.976 0.968 0.979 0.9 41 CLA2: This organization has customer focus strategies. 0.958 CLA3: This organization has learning capacity. 0.975
Culture consistency
CLC1: My organization has core values in its culture. 0.835 0.853 0.911 0.7 74 CLC2: My organization has sustainable agreement. 0.895 CLC3: My organization has coordination and integration
culture.
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Culture involvement
CLI1: My organization has culture of empowerment. 0.848 0.775 0.853 0.5 94 CLI2: My organization has team orientation culture. 0.777 CLI3: My organization has development capability. 0.765 CLI4: My organization has participative culture. 0.684
Culture mission
CLM1: This organization has strategic direction for future. 0.936 0.866 0.906 0.7 63 CLM2: This organization has clear goals and objectives. 0.865 CLM3: This organization has clear vision to achieve goals. 0.815
Dependent decision style
DDS1: When making decision managers need assistance of other employees in my organization.
0.806 0.920 0.944 0.8 09 DDS2: In my organization managers never make decision
without consulting with other employees.
0.955
DDS3: Taking employees support and advice helps managers to make decision.
0.935
DDS4: When top leadership confront with any difficulty, they prefer to get direction from other employees for decision.
0.895
Intuitive decision style
IDS1: In this organization managers rely on intuition for decision making.
0.912 0.890 0.923 0.7 50 IDS2: In this organization managers makes decision based
on their feelings that they believe right to them.
0.838
IDS3: In this organization managers give preference to their own feeling instead of rational reasoning.
0.941
IDS4: In this organization managers use instincts for decision making.
0.762
Innovative capability
INC1: In this organization innovation is essential in business activities.
0.852 0.856 0.912 0.7 76 INC2: In this organization innovation has core value in
business operation.
0.894
INC3: This organization is capable to implement new ideas in operations.
0.896
Organizational performance
OGP1: The productivity of this organization is improving. 0.941 0.894 0.934 0.8 26 OGP2: This organization is benefited by innovative
strategies.
0.874
OGP3: There is significant increase in profit. 0.909
Rational decision style
RDS1: In this organization managers double check information before decision making.
0.913 0.899 0.930 0.7 68 RDS2: As a manager I make decision with logic and careful
thought.
0.856
RDS3: While making decision, managers consider different options for a specific goal.
0.866
RDS4: Decision making requires careful thought and evaluation in all aspects.
0.870
Spontaneous decision style
SDS1: When making decision in my organization, managers act quickly.
0.867 0.881 0.927 0.8 08 SDS2: In my organization managers make spur and
impulsive decision.
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SDS3: In my organization, managers do what they seemnatural to them at that moment.
0.899
Results of the measurement has confirmed constructs reliability, indicator reliability and convergent validity of the constructs. The discriminant validity of the constructs was tested with Fornell and Larcker criteria (Fornell & Larcker, 1981). This method suggest that the square root values of average variance extracted should be higher than other constructs correlation values (Rahi Samar & Abd.Ghani Mazuri, 2019). Findings of the Fornell and Larcker analysis indicate that the square root of average variance extracted (depicted in italic and bold) was higher than the other constructs correlation and therefore confirming the discriminant validity of the construct. Table 2 shows the values of Fornell and Larcker analysis.
Table 2 - Fornell and Larcker’s analysis
A LC C LA C LC C LI C LM D DS ID S IN C O GP R DS S DS A LC 0.8 44 C LA 0.0 19 0.9 70 C LC 0.0 13 0.5 21 0.8 80 C LI 0.0 01 0.0 30 0.0 87 0.7 71 C LM 0.1 39 0.0 68 0.1 43 0.0 57 0.8 73 D DS 0.1 04 0.2 80 0.3 51 0.1 08 0.0 58 0.9 00 ID S 0.0 53 0.2 96 0.3 25 0.1 07 0.0 47 0.2 58 0.8 66 IN C 0.0 19 0.7 70 0.7 08 0.1 50 0.1 71 0.4 37 0.4 68 0.8 81 O GP 0.1 33 0.2 81 0.4 04 0.0 39 0.1 51 0.2 13 0.3 17 0.4 07 0.9 09 R DS 0.0 56 0.5 16 0.5 82 0.0 96 0.1 08 0.3 76 0.4 53 0.6 58 0.3 58 0.8 77 S DS 0.0 16 0.3 23 0.4 08 0.0 02 0.1 06 0.1 82 0.2 73 0.4 59 0.2 14 0.2 95 0.8 99
Note: Bold and italic values indicate square root of the average variance extracted
Although Fornell and Larcker analysis confirms the discriminant validity of the constructs however, it has some deficiencies (Samar Rahi et al., 2020; Rahi Samar & Abd.Ghani Mazuri, 2019). Consequently, the discriminant validity of the constructs was tested with another test namely Heterotrait monotrait ratio analysis introduced by Gold and Arvind Malhotra (2001). The Heterotrait monotrait ratio analysis recommends that in order to achieve discriminant validity the values of HTMT should not be higher than 0.85 or 0.90 (Gold & Arvind Malhotra, 2001; Kline, 2011; Samar Rahi & Abd. Ghani, 2019b). Results indicate that the values of HTMT were lower than threshold value and therefore confirming the discriminant validity of the constructs. Results of the Heterotrait monotrait ratio analysis are shown in Table 3.
Table 3 - Heterotrait-Monotrait ratio analysis
A LC CL A CL C CL I CL M D DS ID S IN C O GP R DS S DS A LC C LA 0.0 41 C LC 0.0 37 0.5 80 C LI 0.0 80 0.0 54 0.1 08
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C LM 0.1 55 0.0 86 0.1 47 0.0 92 D DS 0.1 22 0.2 96 0.3 94 0.1 25 0.0 95 ID S 0.0 61 0.3 00 0.3 49 0.1 21 0.0 46 0.2 74 IN C 0.0 45 0.8 40 0.8 29 0.1 78 0.1 78 0.4 90 0.5 14 O GP 0.1 58 0.3 02 0.4 57 0.0 50 0.1 59 0.2 27 0.3 47 0.4 63 R DS 0.0 67 0.5 57 0.6 64 0.1 20 0.1 06 0.4 12 0.4 84 0.7 48 0.3 92 S DS 0.0 29 0.3 49 0.4 68 0.0 30 0.1 15 0.2 02 0.2 89 0.5 30 0.2 40 0.3 27Finally, the discriminant validity of the variables is tested with cross loading as suggested by Hair Jr, Hult, Ringle, and Sarstedt (2016) and Samar Rahi and Abd. Ghani (2018). Cross loading method suggests that indicator loading should be higher than 0.60 when comparing with other constructs loadings (Fornell & Larcker, 1981; Samar; Rahi et al., 2020). Results indicate that indicator loadings of all factors were higher than other constructs loading and hence confirming discriminant validity of the variables. Table 4 shows the results of the indicator loadings.
Table 4 - Cross loadings method
A LC CL A CL C CL I CL M D DS ID S IN C O GP R DS SD S AL C1 0.8 16 -0.022 -0.013 0.0 10 0.1 42 -0.092 0. 031 -0.030 0. 116 0. 051 0.0 17 AL C2 0.8 34 0.0 23 0.0 42 0.0 37 0.1 01 -0.094 0. 058 0.0 20 0. 105 0. 066 0.0 09 AL C3 0.8 82 -0.045 0.0 06 -0.046 0.1 08 -0.077 0. 046 -0.035 0. 115 0. 028 0.0 15 CL A1 -0.018 0.9 76 0.5 03 0.0 41 0.0 60 0.2 85 0. 299 0.7 52 0. 283 0. 535 0.3 06 CL A2 -0.028 0.9 58 0.5 29 0.0 00 0.0 67 0.2 65 0. 294 0.7 49 0. 270 0. 478 0.3 15 CL A3 -0.009 0.9 75 0.4 85 0.0 46 0.0 72 0.2 63 0. 268 0.7 40 0. 265 0. 489 0.3 19 CL C1 0.0 06 0.6 51 0.8 35 0.0 48 0.0 65 0.2 70 0. 198 0.5 92 0. 256 0. 523 0.2 96 CL C2 0.0 36 0.3 50 0.8 95 0.0 95 0.1 60 0.3 53 0. 336 0.6 28 0. 431 0. 483 0.3 67 CL C3 -0.007 0.3 89 0.9 07 0.0 86 0.1 47 0.3 01 0. 317 0.6 48 0. 373 0. 531 0.4 08 CL I1 0.0 57 0.0 53 0.0 73 0.8 48 0.0 61 0.0 72 0. 101 0.1 45 0. 024 0. 059 -0.001 CL I2 0.0 29 -0.032 0.1 32 0.7 77 0.1 06 0.1 45 0. 062 0.1 05 0. 067 0. 063 0.0 32 CL I3 -0.079 0.0 35 0.0 18 0.7 65 0.0 07 0.0 86 0. 087 0.1 20 0. 019 0. 088 -0.015 CL I4 -0.030 0.0 26 0.0 49 0.6 84 -0.010 0.0 23 0. 075 0.0 76 0. 012 0. 103 -0.011 CL M1 0.1 44 0.1 10 0.1 47 0.0 25 0.9 36 0.0 76 0. 068 0.1 96 0. 170 0. 149 0.0 84 CL M2 0.1 05 0.0 29 0.1 23 0.0 83 0.8 65 0.0 02 0. 012 0.1 24 0. 084 0. 031 0.1 26 CL M3 0.0 97 -0.070 0.0 56 0.0 82 0.8 15 0.0 88 0. 011 0.0 42 0. 124 0. 050 0.0 58 D DS1 -0.093 0.3 74 0.3 11 0.0 95 -0.029 0.8 06 0. 140 0.3 75 0. 128 0. 352 0.1 61
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D DS2 -0.091 0.2 28 0.3 26 0.1 12 0.0 96 0.9 55 0. 287 0.4 36 0. 228 0. 347 0.1 56 D DS3 -0.091 0.2 40 0.3 37 0.0 87 0.0 88 0.9 35 0. 262 0.4 15 0. 227 0. 343 0.1 84 D DS4 -0.099 0.1 62 0.2 82 0.0 95 0.0 41 0.8 95 0. 227 0.3 32 0. 173 0. 308 0.1 52 ID S1 0.0 63 0.2 45 0.2 54 0.1 04 0.0 13 0.2 25 0. 912 0.3 96 0. 280 0. 382 0.2 01 ID S2 0.0 45 0.3 54 0.3 79 0.0 90 0.0 80 0.2 25 0. 838 0.4 94 0. 278 0. 473 0.3 27 ID S3 0.0 49 0.2 29 0.2 75 0.1 14 0.0 42 0.2 70 0. 941 0.4 12 0. 294 0. 389 0.2 31 ID S4 0.0 19 0.1 36 0.1 52 0.0 47 0.0 06 0.1 49 0. 762 0.2 49 0. 239 0. 272 0.1 30 IN C1 -0.035 0.9 13 0.5 79 0.1 01 0.0 87 0.3 35 0. 318 0.8 52 0. 269 0. 580 0.3 32 IN C2 0.0 14 0.5 45 0.6 32 0.1 46 0.1 93 0.4 40 0. 471 0.8 94 0. 435 0. 560 0.4 13 IN C3 -0.029 0.5 62 0.6 63 0.1 52 0.1 74 0.3 81 0. 451 0.8 96 0. 374 0. 597 0.4 73 O GP1 0.1 12 0.2 54 0.3 67 0.0 23 0.1 31 0.1 54 0. 244 0.3 51 0. 941 0. 322 0.1 88 O GP2 0.1 08 0.2 58 0.4 11 0.0 56 0.1 71 0.2 85 0. 376 0.4 19 0. 874 0. 369 0.2 13 O GP3 0.1 45 0.2 52 0.3 15 0.0 24 0.1 03 0.1 29 0. 232 0.3 30 0. 909 0. 277 0.1 79 R DS1 0.0 29 0.6 07 0.5 11 0.0 54 0.0 55 0.3 09 0. 332 0.5 83 0. 275 0. 913 0.2 24 R DS2 0.0 69 0.3 20 0.5 31 0.1 47 0.1 42 0.3 90 0. 495 0.5 94 0. 383 0. 856 0.2 87 R DS3 0.0 53 0.3 51 0.5 32 0.0 87 0.1 23 0.3 12 0. 475 0.5 94 0. 364 0. 866 0.3 47 R DS4 0.0 46 0.5 45 0.4 61 0.0 45 0.0 54 0.3 04 0. 272 0.5 30 0. 222 0. 870 0.1 64 SD S1 0.0 35 0.3 29 0.3 53 0.0 00 0.0 60 0.1 34 0. 284 0.4 15 0. 208 0. 271 0.8 67 SD S2 0.0 10 0.2 79 0.3 98 -0.016 0.1 17 0.1 87 0. 238 0.4 23 0. 181 0. 273 0.9 29 SD S3 -0.001 0.2 61 0.3 48 0.0 23 0.1 09 0.1 69 0. 211 0.4 00 0. 189 0. 250 0.8 99Note: Indicator loadings are shown in bold and italic
4.2 Structural model
Following first stage of the structural equation modeling, the validity and reliability of the constructs was tested with measurement model. Therefore, in second stage researcher has examined the structural path and coefficient of determination with t-statistics (S Rahi, Ghani, & Ngah, 2018). The measurement model has tested vertical multicollinearity therefore, the multicollinearity of the constructs is tested with variance inflation factor analysis in line with S Rahi, Ghani, Alnaser, and Ngah (2018) and Hair Jr et al. (2016). The variance inflation factor analysis suggests that the values of VIF must be lower than 3.3 when comparing with other constructs. Results depict that VIF values were lower than threshold value and therefore indicating adequate lateral multicollinearity of the constructs. The results of the variance inflation factors are exhibited in Table 5.
Table 5 - Assessing lateral multicollinearity
Constructs Innovative Capability Organizational Performance
Allocentrism 1.000
Culture Adaptability 1.549
Culture Consistency 1.851
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Culture Mission 1.028
Dependent Decision Style 1.221
Intuitive Decision Style 1.314
Innovative Capability 1.000
Rational Decision Style 1.908
Spontaneous Decision Style 1.257
4.2.1 Hypothesis testing
For hypotheses testing data were bootstrapped with resample of 3000 as suggested by Samar, Ghani, and Alnaser (2017). Table 6 depicts results of all hypotheses with path coefficient (β), standard error, t-statistics, and significance level of the proposed hypotheses.
Table 6 - Hypotheses testing
Findings of the structural model confirms that culture adaptability had positive and significant influence in innovative capability and supported by H1: (β= 0.463path coefficient, t-statistics 8.185, significance at p < 0.001). Culture mission had significant influence in innovative capability and supported by H2: (β=0.061, t-statistics 2.670, significance at p < 0.001). Culture involvement had shown significant influence in innovative capability and statistically confirmed by H3: (β=0.073, t-statistics 3.176, significance at p < 0.001). Similarly, culture consistency had positive influence in innovative capability and confirmed by H4: (β=0.256, t-statistics 4.670, significance at p < 0.001). Concerning with decision making constructs, findings showed that intuitive decision had positive influence in innovative capability and supported by H5: (β=0.121, t-statistics 3.542, significance at p < 0.001). In addition to that rational decision style had shown positive influence in innovative capability and statistically supported by H6: (β=0.129, t-statistics 2.957, significance at p < 0.001). Dependent decision style had shown positive and significant influence in innovative capability and supported by H7: (β=0.107, t-statistics 3.399, significance at p < 0.001). Spontaneous decision style had shown significant influence in innovative capability and confirmed by H8: (β=0.108, t-statistics 3.216, significance at p < 0.001). Finally, the relationship between innovative capability and organizational performance was found significant and supported by H9: (β=0.409, t-statistics 6.563, significance at p < 0.001). These findings confirmed that the research model has substantial power to predict organizational innovative capability and organizational performance. The results of the structural equation modeling are depicted in appendix 1.
4.2.2 The predictive relevance 𝐐𝟐, coefficient of determination (𝐑𝟐) and effect sizes (𝐟𝟐)
The predictive relevance of the research model is assessed with blind-folding procedure 𝑄2 as suggested by S.
Rahi (2017). In order to achieve adequate predictive relevance criterion is that the values of blind-folding procedure 𝑄2 must be higher than 0 in line with S. Rahi (2017). Findings indicate that for both endogenous variables the
values of blind-folding procedure 𝑄2 were found substantial. Similarly, innovative capability was measured by
Hypothes is Relationshi p Direct effect (β) Standard deviation T-statistics Significanc e H1 CLA -> INC 0.463 0.057 8.185 0.000 H2 CLM -> INC 0.061 0.023 2.670 0.004 H3 CLI -> INC 0.073 0.023 3.176 0.001 H4 CLC -> INC 0.256 0.055 4.670 0.000 H5 IDS -> INC 0.121 0.034 3.542 0.000 H6 RDS -> INC 0.129 0.044 2.957 0.002 H7 DDS -> INC 0.107 0.031 3.399 0.000 H8 SDS -> INC 0.108 0.034 3.216 0.001 H9 INC -> OGP 0.409 0.062 6.563 0.000
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culture adaptability, culture mission, culture involvement, culture consistency, intuitive decision style, rational decision style, dependent decision style and spontaneous decision style and explained substantial variance 𝑅279.7% in innovative capability. Authors like S Rahi, Ghani, and Ngah (2018) argued that coefficient of determination 𝑅2 shows collective variance however, it lacks individual effect size which can be determined
through effect size analysis (𝑓2). Findings of the effect size analysis shows that culture adaptability had substantial
effect size in predicting innovative capability. Therefore, culture consistency had medium level of effect size in determining innovative capability. Concerning with organization performance, findings indicate that innovative capability had medium effect size in measuring organizational performance. Results of the effect size analysis, predictive relevance and coefficient of determination are exhibited in Table 7
Table 7 - Coefficient of determination, predictive relevance, and effect size Innovative Capability
Constructs 𝑅2 𝑄2 𝑓2 Results
Innovative Capability 79.7% 0.604
Culture Adaptability 0.682 Substantial
Culture Consistency 0.174 Medium
Culture Involvement 0.026 Small
Culture Mission 0.018 Small
Dependent Decision Style 0.046 Small
Intuitive Decision Style 0.055 Small
Organizational Performance
Constructs 𝑅2 𝑄2 𝑓2 Result
Organizational Performance 20.7% 0.154
Allocentrism 0.025 Small
Innovative Capability 0.211 Medium
Note: Effect size 0.35, Substantial; for Medium; 0.15 and 0.02 indicates Small
4.3 The importance and performance analysis
The objective of this study is determined organizational innovative capability and organizational performance. Therefore, the complexity of the research model requires to determine factors importance and performance with importance performance matrix analysis (Mohammed Ali Yousef Yamin, 2019; Mohammad Ali Yousef Yamin & Alyoubi, 2020). According to S Rahi, Ghani, and Ngah (2018) importance performance matrix analysis adds an additional dimension into data analysis and should be considered. Following guideline provided by S Rahi, Ghani, and Ngah (2018) researcher has employed importance performance matrix analysis. For importance performance matrix analysis, we took organizational performance as an outcome variable. Findings indicate that innovative capability has the highest importance to predict organizational performance. Therefore, constructs like allocentrism, culture consistency and culture adaptability has shown intermediate level of importance. Concerning with other constructs such as institutive decision making style, rational decision making style, spontaneous decision making style, dependent decision making style and culture involvement have shown low importance in determining organizational performance. The results of the importance performance matrix analysis are depicted in Table 8.
Table 8 - Importance and performance using IPMA
Constructs Importance /Total effect of organizational performance Performance index of organizational performance Allocentrism 0.165 60.358 Culture Adaptability 0.185 71.314 Culture Consistency 0.114 65.846 Culture Involvement 0.020 77.757 Culture Mission 0.026 68.087
Dependent Decision Style 0.045 60.008
Intuitive Decision Style 0.051 61.408
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Rational Decision Style 0.057 59.804
Spontaneous Decision Style 0.046 63.212
The importance and performance of the construct can be examined using importance performance map as depicted in Fig.2. Importance performance map clearly shows that culture involvement has the highest performance, but it may not be an important construct for managerial implications. IPMA map clearly shows that culture involvement, culture mission and decision-making style had shown lowest importance. Thus, findings of the importance performance matrix analysis conclude that constructs like innovative capability, allocentrism, culture adaptability and culture consistency are the most potential construct for managerial consideration.
Fig2- Importance and performance analysis map
4.4 Moderating analysis
The current research examines the moderating role of allocentrism with relation to innovative capability and organizational performance. The moderating relationship of allocentrism is underpinned in such a way that the relationship between innovative capability and organizational performance is stronger when allocentrism is higher. For empirical findings, we have followed product indicator approach consistent with earlier studied Samar Rahi (2015, 2016); Samar Rahi and Ghani (2016). Results of the moderating analysis revealed that allocentrism is moderate the relationship between innovative capability and organizational performance and supported by H10 (β = 0.153, t-statistics 2.240, significant at p < 0.05). Statistical findings are given in Fig.3 comprising path coefficient and t-statistics.
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Fig.3 - Statistics of moderating analysisStatistical findings have confirmed that allocentrism moderate the relationship between innovative capability and organizational performance. However, the strength of the moderating relationship is estimated with simple slope analysis. Simple slope analysis help researcher to understand moderating trend through gradient. Results indicate that allocentrism (ALC) at +1SD depicts positive and upward gradient when it is compared with allocentrism (ALC) at -1SD shows descending and negative gradient. These findings confirmed that the moderating relationship between innovative capability and organizational performance will be stronger when allocentrism is higher. Simple slope analysis is depicted in Fig 4.
Fig.4 Simple slope analysis for moderating effect
5 Discussion
This study attempts to gain insight factors which influence organizational innovation capability and organizational performance. After detailed literature review an integrative research model was developed that underpinned organizational culture, decision style and allocentrism. Structural equation modeling approach was employed to test the causal relationship among variables. Results revealed that culture adaptability has positive and significant influence in innovative capability and consistent with Lasrado and kassem (2020). Culture mission has significant influence in innovative capability and in line with earlier studies Botelho (2020); D. Denison et al.
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(2014); D. R. Denison and Mishra (1995). Culture involvement and culture consistency have significant influence in innovative capability and supported by earlier studies Botelho (2020); Boyce et al. (2015); D. Denison et al. (2014); Lasrado and kassem (2020). Referring to decision making constructs, findings showed that intuitive decision and rational decision style had shown positive influence in innovative capability and consistent with earlier studies Abubakar et al. (2019); Verma et al. (2015). Moreover, dependent decision style and spontaneous decision style have revealed significant influence in innovative capability and in line with Abubakar et al. (2019); Appelt et al. (2011); Verma et al. (2015). The relationship between innovative capability and organizational performance was found significant and consistent with earlier studies (Aktaş, 2014; Gabel-Shemueli et al., 2019; Nahum-Shani & Somech, 2011). Concerning with moderating role of allocentrism, results have confirmed that moderating relationship between innovative capability and organizational performance will be stronger when allocentrism is higher. These findings have confirmed that the newly developed research model has substantial power to predict organizational innovative capability and organizational performance.5.1 Theoretical implications
This research contributes to theory and literature in numerous ways. First, the research model of this study outlined Denison’s organizational culture dimensions D. R. Denison and Mishra (1995) to investigate organizational innovative capability. Prior studies have focused on work engagement and business excellence. Therefore, the current research investigates Denison’s organizational culture model in the context of organizational innovative capability and consequently contribute to organizational innovative literature. Second, the decision making styles are considered as antecedents of organizational innovative capability. Findings have confirmed significant relationship between decision styles and organizational innovative capability and enrich literature in this context. In addition to that organizational innovative capability was measured through an integrative perspective research model that combines factors underpinned organizational culture and decision style and explained substantial variance 𝑅2 79.7% in determining organizational innovative capability. Finally, the
moderating role of allocentrism was confirmed in such a way that it strengthens the relationship between organizational innovative capability and organizational performance when allocentrism is higher. These findings enrich the human resource literature and contribute to organizational culture model.
5.2 Practical implications
Findings of this research provides several directions to managers and policy makers. First, this research suggests that right managerial decisions and consistent organizational culture boost organizational innovative capability and organizational performance. Moreover, findings indicate that culture adaptability has substantial effect size in predicting innovative capability. Therefore, managers and policy makers should introduce culture adaptability practices in their organization which in turn enhance organizational performance. For managerial implications, researcher took help from importance performance matrix analysis. Results of the performance matrix analysis showed that innovative capability is the most influential factor for managerial consideration. In addition to that managers should concentrate on constructs like culture consistency and culture adaptability to bring excellence in business. In extended research model, this study suggests that both allocentrism and innovative capability have considerable effect size in measuring organizational performance. Thus, managers and policy maker should design business strategies comprising allocentrism and innovative attributes.
6 Conclusion
In today’s volatile and uncertain business environment innovation and excellence are considered the most potential factors that can enhance organizational performance. In this sense, the current research attempts to examine factors which influence on organization innovative capability and organizational performance. An integrative perspective research model is developed that underpinned factors such as organizational culture, decision making style and allocentrism to predict organizational innovative capability and organizational performance. Using structural equation modeling, this research revealed that altogether culture adaptability, culture mission, culture involvement, culture consistency, intuitive decision style, rational decision style, dependent decision style and spontaneous decision style explained substantial variance 𝑅2 79.7% in innovative capability.
Extending to this the effect size analysis (𝑓2) showed that culture adaptability has substantial power when
measuring organizational innovative capability. Therefore, culture consistency is identified as second most important factor in determining organizational innovative capability. This study has tested predictive relevance of the model to predict organizational innovative capability using blind-folding procedure 𝑄2. Therefore, results
indicate substantial power 60.4% to predict organizational innovative capability. In extended research model, this study disclosed that allocentrism moderate the relationship between organizational innovative capability and organizational performance. Theoretically, this research contributes to organizational culture and decision making style literature in the context of innovative capability. Therefore, for managerial implications, research took help from importance performance matrix analysis. Results of the importance performance matrix analysis suggest that
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managers should focus on allocentrism, culture adaptability and culture consistency and innovative capability to enhance organizational performance.6.1 Research limitations and future research directions
Despite several contributions to theory and practice, this study has some limitations that imputes future research directions. First, this study examines organizational innovative capability with an integrated research model that underpinned dimensions of organizational culture and decision making style. Therefore, it does not guarantee to include all factors that influence on organizational innovative capability and organizational performance. This research is cross section and collects data at one point of time. Therefore, caution is required in interpreting the findings as results may differ in longitudinal context. Another limitation of this study is related to data sample which was collected only from well-established organizations. Future research may include sample data from small medium enterprises. As this study is focused on positive decision styles, consequently avoidant decision style was dropped in research model. Future studies may add avoidant decision style in the research model to see how positive and negative decision styles impact organizational capability. Finally, this study is limited to Saudi region nevertheless, future researcher may replicate current research model in developing countries to get divers findings.
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