This work investigates whether management accountants (MA) who have experience of working in multicultural environments are more open to share their knowledge, learning and insights with others or not. The study was conducted in early 2018 by using a Partial Least Squares-Structural Equation Modeling (PLS-SEM) technique with a sample of 107 MAs working in India in 7 different cities and in different multinational organizations. The research identified that coopetition mediated the relationship between cultural intelligence (CQ) and the intention to share knowledge (ISK) as evidenced by both PLS-SEM and fsQCA methods. This finding is significant for both theory and practice as coopetition involves both collaboration and completion amongst the MAs. The Multi Group Analysis (MGA) revealed no significant gender related differences amongst the practicing management accountants. The study also contributes to the methods by illustrating the modelling of the second order construct “cultural intelligence”, formatively. Thus, this study illustrates the use of second order reflective-formative constructs in management accounting literature, for exploring the theory. This architecture can be of significant use for future researchers.
Cultural Intelligence Management Accountant Coopetition Intention to Share Knowledge PLS-SEM fsQCA1. Introduction
According to Ang and Van Dyne [1] , cultural intelligence (CQ) is the “capability of an individual to function effectively in situations characterized by cultural diversity”. Professionals such as management accountants (MA) need to develop cross-cultural skills and competencies [2] to function effectively in a multi-cultural work environment. As per extant literature, culturally intelligent people have the understanding and appreciation of their primary culture and the curiosity and willingness to learn and appreciate new cultures and norms [3] . Although coopetition, a blending of cooperation and competition, is a paradigm originally applied for inter-firm relationships, this study however uses the paradigm of coopetition at the individual level MAs.
Management accountants (MA) in their role as knowledge workers are engaged in operational and strategic decision making for their firms by drawing insights from all data including big data [4] . MAs, to be informed and effective, prefer to connect professionally by using mobile technologies [5] and may also get influenced by the relevant data from social media [6] , just like any other individual. This study considers only those MAs who have experience of working in multicultural environments and thus are expected to be culturally sensitive and aware. This is because prior works such as those by Crowne [7] suggest that work related international experience is related to CQ and engagement increases by interaction with people [8] .
Through this study, it was probed whether these MAs are open to share their knowledge and experience which they have gained after working in multiple geographies with other stakeholders especially their organizational peers. The study was conducted in early 2018 using a partial least square-structural equation modeling technique with a sample of 107 MAs working in different multinational organizations in 7 cities in India. To the best of author’s knowledge, the understanding about the manifestations of cultural intelligence on information sharing intention of MAs is yet to be explored in the emerging market context. The extant literature has evidence about the managers being influenced by CQ in thinking strategically [9] ; still fresh insights are needed about the role of CQ on the MAs’ intention to share knowledge in the ever evolving emerging market context.
The findings of the study make certain key contributions.
・ First, the research identified that coopetition mediates the relationship between cultural intelligence and the intention to share knowledge.
・ Second, the multi group analysis (MGA) revealed no significant gender related difference amongst the practicing management accountants.
・ Third, the study contributes to the methods by illustrating the modelling of the second order construct “cultural intelligence”, formatively and validating it by fsQCA also. This is a key contribution to the methods literature in the management accounting research domain.
Post the introduction, the paper starts with the conceptual development and hypothesis which is followed by the discourse on methods. The following chapters highlight the results, the detailed discussion on the findings and the conclusion of the paper.
2. Conceptual Development and Hypothesis
Prior insightful works such as by Tharapos et al. [9] have contributed substantially towards the appreciation of cultural intelligence (CQ) in specific contexts (such as accounting academics) by extending the knowledge about the antecedents of CQ, thereby encouraging the exploration of this concept in hitherto under explored contexts. Other significantly notable contexts in which the CQ theme has been studied includes military [10] , international managers [11] and students [12] .
Cultural intelligence has four themes metacognitive, cognitive, motivational and behavioral all of which are equally important [13] . The metacognitive CQ entails the reflection on one’s own thinking process with the help of cultural knowledge whereas cognitive CQ is the knowledge of cultural norms, values etc. acquired through education and experience [1] . As per Ang and Van Dyne [1] motivational CQ entails an individual’s perseverance, interest etc. to function in a culturally diverse and challenging environment and behavioral CQ includes verbal and non-verbal behavior as expressed by individuals in dealing with people from different cultures. CQ is positively associated with cultural adjustment [12] , with global leadership performance [14] and personality traits [15] . Previous works such as those by Engle and Crowne [16] have suggested that gender is insignificant in the comprehensive CQ model. However, there is a requirement to revisit this finding in the emerging market context given the unique socio-cultural background of these emerging economies.
Nonaka [17] opined that the knowledge management system aims to enhance the sharing of learnings and insights among the employees which leads to collective knowledge sharing in the organization. Nonaka [17] also highlighted the role of technology in this process. Knowledge itself has been defined by Sanchez and Heene [18] as “a set of beliefs held by an individual about the causal relationships among phenomena”. These beliefs are refined with formal experience and informal exchanges. Hansen [19] suggested that individual, person to person interaction, say in meetings, leads to knowledge sharing in firms. Felicio et al. [20] further suggested that individuals store and use information in records and databases and also share the key learning thereby creating new knowledge. Knowledge management and its impact on knowledge sharing intention have been studied in detail by He and Wei [21] . Baskerville [22] asserted the need for an individual information system and Brazelton and Gorry [23] opined the relevance of individual beliefs and motivations for the same.
A deeper understanding and appreciation of the coopetition concept is made by Bouncken and Fredrich [24] who study collaboration and completion together through “trust and dependency” lens. Other prior works have also conclusively pointed out the coopetition promises strong advantages [25] which suggest the need to study this concept at the individual level as well. This study probes the interesting research question as to whether coopetition has any role to play in the linkage between cultural intelligence (CQ) and intention to share knowledge (ISK) amongst the MAs. The entire above discussion leads to the following hypothesis:
H1a: Coopetition mediates the relationship between behavioral factor of cultural intelligence and the intention to share knowledge.
H1b: Coopetition mediates the relationship between cognitive factor of cultural intelligence and the intention to share knowledge.
H1c: Coopetition mediates the relationship between metacognitive factor of cultural intelligence and the intention to share knowledge.
H1d: Coopetition mediates the relationship between motivational factor of cultural intelligence and the intention to share knowledge.
H2: Gender of the management accountant does not impact the intention to share knowledge.
3. Methods3.1. Data Collection, Research Setting, and Sample
The hypothesis was tested on the data generated from 107 management accountants from pan India multinational companies, so that the results could be generalized [26] . The respondents were informed beforehand that the data was being collected for academic research and that they should give honest responses. A pretested questionnaire [27] was validated by pilot study [28] and was administered to the MAs. A seven point Likert scale (where 1 = strongly disagree and 7 = strongly agree) was used to maximize the variances. The survey questionnaire was given to 350 MAs and a final usable response of 107 participants was obtained. Thus, the response rate was 30.57%. The author used the hard copy of the questionnaire and also undertook a follow up procedure involving two contacts with the MAs who had not responded. It was ensured that the sample mirrors the actual population of MAs in India.
As per Varma 2018 [4] MAs were defined as those professionals who were designated by their respective organizations as such and were primarily responsible for either one or more sub-domains such as cost and financial accounting, management audit, legal, taxation, or compliance work. Non accounting professionals were very carefully screened out from the sample. Only those MA who had served for at least one year in geography different from their place of domicile [29] and with a minimum of three years of work experience were considered for the purpose of the study. Those MAs who had served in the sister concerns of the same group were also considered for this study. The face validity of the questionnaire was established by taking the expert opinion of 3 academics and 3 industry practitioners from the general management domain. The sample description is given in Table 1. To ensure that there is no common method bias, guidelines of Podsakoff et al. [30] were followed. All the respondents were assured of complete anonymity and also explicitly told that the responses will be used for academic research only thereby ensuring honest responses.
Sample description, n = 107
Variable
Values
%
Age
25 - 35
34.57%
36 and above
65.42%
Gender
Male
62.61%
Female
37.38%
Educational background
Professional qualification, such as a degree in Chartered Accountancy, Cost Accountancy, Company Secretary, ACCA, and CIMA Master’s level qualification in commerce and allied disciplines, with a specialization in Accountancy, Information Technology, or allied disciplines
85.98% 14.01%
As per Chin [27] when a regression heuristic of 10 cases per indicator are used, then the sample size needed is ten times the largest number of formative indicators or the largest number of independent variables which impact a dependent variable―whichever of the two is higher in number. Thus, the sample size was adequate for the purpose of undertaking this study. Hwang et al. [31] suggest that accounting professionals need training on specific dimensions such as information formality. As advocated by Hwang et al. [31] , this study also surveyed accounting professionals with a homogenous sampling method to help in generalization of the findings. Further, Hwang et al. [31] assert “accounting professionals are constantly engaged in knowledge inquiry and problem solving tasks; they often rely on documentation templates and previous deliverables to complete a task at hand. For example, auditors use prior year working papers as a baseline to complete the current year’s audit”. Other prominent works by noted authorities such as Chong [32] had also advised further probe of knowledge sharing in the accounting domain. This study was an attempt in this direction.
3.2. Statistical Analysis
For data analysis, a partial least-square structured equation model (PLS-SEM) is the best choice as this is an exploratory study and PLS SEM can measure the formative constructs also. PLS SEM does not have any assumptions regarding the normal distribution of data. PLS-SEM also does not suffer from identification problems due to small sample sizes. In the present context, PLS-SEM is reliable as the technique comprises a non-parametric multivariate analysis that simultaneously measures both the structural and the measurement models [33] [34] . The Smart PLS package version 3.2.7 [35] was employed for the data analysis.
3.3. Measurement Variables
All responses, including coopetition were taken on a 7 point Likert scale. This study used the CQS scale by Ang et al. [11] . The cultural intelligence CQ scale which is the most popular method of assessing cross-cultural competency [36] is reliable [11] . The scale for the construct intention to share knowledge (ISK) was taken from He and Wei [21] . The three item scale for the construct coopetition (COOP) was taken from Bouncken and Friedrich [24] .
4. Results
The results were obtained by analyzing the measurement and structural models as demonstrated by prior works such as those by Ali and Park (2016) [37] . It was adequately ensured that the constructs were well-measured for subsequent evaluation of the structural model.
4.1. Evaluation of the Measurement Model
All the constructs in the model were reflectively measured except for the construct “cultural intelligence” which was measured formatively. Cultural intelligence construct has a formative measurement as the first order constructs are defining characteristics of the second-level constructs and if one of the first order construct is removed then the conceptual domain of the second order construct “cultural intelligence” is changed [38] . This type of model which has the second order construct as a formative measurement along-with the first order construct which has a reflective measurement are referred to as type II models [39] .
Composite reliability (CR) (Table 2) estimates the internal consistency of the constructs. The CR was greater than 0.7 and Cronbach’s alpha (Nunnally 1978) [40] was also more than 0.7 (except for coopetition for which it was 0.655 and thus close to 0.7) for all the constructs. The outer loadings were higher than or close to 0.7 (except BEH 1, CO1 and CO2 which were retained due to the theoretical underpinning) and were significant at 95% level. The measure of convergent validity, average variance extracted (AVE) was greater than 0.5 and significant at the 95% level. The Heterotrait Monotrait ratio (HTMT), which is more rigorous than the Fornell and Larcker [41] criteria were used to determine the discriminant validity. Since the HTMT ratio (Table 3) was generally below 0.85 (except Cultural Intelligence and Behavior where it was marginally above this threshold), the discriminant validity was established. With the above reliable and valid constructs (Table 2), all the constructs were used for overall assessment of the structural model.
Prior to the modelling of the construct cultural intelligence formatively, it was required to do a redundancy analysis with a single global measure, the calculation of outer and inner VIF (Table 4 and Table 5) for the cultural intelligence construct (which were all less than 5) and ascertaining the significance of the outer weights of the cultural intelligence construct. Thus, the construct cultural intelligence could be measured formatively as a second order construct.
4.2. Evaluation of the Structural Model
To undertake the structural model assessment, a collinearity check was carried out [42] . This was measured with the help of the variance inflation factor (VIF) for each construct, and it was found to be less than 5, indicating that multi-collinearity was not present [43] . The outer and inner VIF values are given in Table 4 and Table 5, respectively.
Reliability and validity
Construct
Items
Factor Loadings
CR
Cronbach Alpha
AVE
Behaviour
0.847
0.771
0.532
BEH1
0.480
BEH2
0.804
BEH3
0.790
BEH4
0.765
BEH5
0.760
Coopetition
0.800
0.655
0.575
CO1
0.642
CO2
0.836
CO3
0.782
Cog
0.873
0.826
0.537
COG1
0.714
COG2
0.611
COG3
0.797
COG4
0.829
COG5
0.712
COG6
0.715
Intention to share knowledge
0.889
0.750
0.800
ISK1
0.897
ISK2
0.892
MC
0.877
0.814
0.642
MC1
0.754
MC2
0.801
MC3
0.843
MC4
0.804
MOT
0.911
0.877
0.671
MOT1
0.816
MOT2
0.817
MOT3
0.850
MOT4
0.819
MOT5
0.792
CR = composite reliability; Ave = average variance extracted.
Heterotrait Monotrait ratio (HTMT)
Heterotrait-Monotrait Ratio (HTMT)
BEH
COG
COOP
CUL INTEL
ISK
MC
MOT
BEH
COG
0.395
COOP
0.584
0.250
CUL INTEL
0.929
0.808
0.570
ISK
0.682
0.252
0.627
0.698
MC
0.582
0.446
0.358
0.866
0.492
MOT
0.670
0.332
0.579
0.878
0.753
0.544
Outer VIF values
Outer VIF Values
VIF
BEH1
1.129
BEH1
1.511
BEH2
1.845
BEH2
2.507
BEH3
1.827
BEH3
2.019
BEH4
1.818
BEH4
2.141
BEH5
1.769
BEH5
2.222
CO1
1.343
CO2
1.191
CO3
1.462
COG1
1.449
COG1
1.726
COG2
1.382
COG2
1.600
COG3
2.135
COG3
2.450
COG4
2.453
COG4
2.919
COG5
1.595
COG5
1.858
COG6
1.563
COG6
1.721
ISK1
1.562
ISK2
1.562
MC1
1.531
MC1
1.709
MC2
1.703
MC2
2.292
MC3
1.975
MC3
2.318
MC4
1.687
MC4
2.328
MOT1
2.173
MOT1
2.753
MOT2
2.178
MOT2
2.490
MOT3
2.343
MOT3
2.751
MOT4
2.085
MOT4
2.571
MOT5
1.840
MOT5
2.065
Inner VIF values
Inner VIF Values
BEH
COG
COOP
CUL INTEL
ISK
MC
MOT
BEH
1.604
COG
1.206
COOP
1.303
CUL INTEL
1.000
1.303
ISK
MC
1.482
MOT
1.568
The path coefficients (all are significant at 95% level) are shown in Figure 1 and in Table 6. The PLS algorithm aims to reject a set of path-specific null hypothesis of no effect. The “R square” value 0.429 was sufficiently high (Table 7). As seen in Table 8 (path coefficients), motivation factor of cultural intelligence had the highest direct effect as an antecedent for cultural intelligence (β = 0.464****, t = 11.172).
Significant individual path coefficients in the structural model
Structural Path
Path Coefficient (t Value)
p Values
Conclusion
BEH -> CUL INTEL -> COOP -> ISK
0.043 (2.346)
0.019
H1a is supported
COG -> CUL INTEL -> COOP -> ISK
0.030 (2.102)
0.036
H1b is supported
MC -> CUL INTEL -> COOP -> ISK
0.034 (2.264)
0.024
H1c is supported
MOT -> CUL INTEL -> COOP -> ISK
0.059 (2.279)
0.023
H1d is supported
Gender and knowledge sharing
From the multi group analysis
H2 is supported
R square
R Square
R Square
R Square Adjusted
COOP
0.233
0.225
ISK
0.429
0.418
Path coefficients
Path Coefficients
Original Sample (O)
t Statistics (|O/STDEV|)
p Values
BEH -> CUL INTEL
0.337
8.904
0.000
COG -> CUL INTEL
0.240
4.269
0.000
COOP -> ISK
0.262
2.819
0.005
CUL INTEL -> COOP
0.482
6.000
0.000
CUL INTEL -> ISK
0.488
5.077
0.000
MC -> CUL INTEL
0.272
6.854
0.000
MOT -> CUL INTEL
0.464
11.172
0.000
n.s.: not-significant; * |t| ≥ 1.65 at p = 0.10 level; ** |t| ≥ 1.96 at p = 0.05 level; *** |t| ≥ 2.58 at p = 0.01 level; **** |t| ≥ 3.29 at p = 0.001 level.
4.3. Importance-Performance Map Analysis (IPMA)
The performance of the construct “Cultural Intelligence” was the lowest at 64.906 (Table 9). This result means that there is the highest scope for improvement in this construct. The findings suggest that since cultural intelligence is also the most impactful construct (Table 10) (total effect = 0.614) and has the least performance (Figure 2), further improvement of the MAs cultural intelligence is a worthy goal to be pursued by the firms which is an important contribution of this study.
4.4. Multi Group Analysis (MGA) on the Basis of Gender
Morris et al. [44] suggested that gender differences in behavior intentions merit is yet to be probed, and thus, the MAs views on knowledge sharing was ascertained with regard to the gender. As per the multi group analysis based on the gender of the respondents, it was found that there was no difference on the basis of gender in the mediating role of coopetition in the linkage between cultural intelligence and the intention to share knowledge. As given in Table 11, all the p values in the parametric test are non-significant (with the exception of BEH -> CUL INTEL).
4.5. Blindfolding
The degree of predictive relevance of the exogenous constructs for the endogenous construct intention to share knowledge, which was measured reflectively, was estimated with the Q square value, which is calculated using the blindfolding procedure [42] . Since Q square is greater than 0, the model has predictive relevance, and a significant amount of variance is explained by our model (Table 12).
4.6. fsQCA Results
The method of fsQCA provides combination of causal themes associated with the intention to share knowledge. The result of the fsQCA reveals that all of the items of the construct coopetition are necessary conditions for the intention to share knowledge. This study also builds on prior significant works by Ragin [45] who asserted that fsQCA helps distinguish between necessary conditions and sufficient causal conditions and that fsQCA used consistency and coverage index to evaluate antecedents and their combination. Other experts such as Fiss [46] asserted that fsQCA uses a fuzzy set theory and Boolean logic for testing causal asymmetry and Ganter and Hecker [47] suggested that fsQCA deals with high level of causal complexity. For the purpose of fsQCA, this study did not average out all the items of the constructs but took them at the individual level to discover more information about the intention to share knowledge (Table 13).
There are many advantages of coopetition. As per Miotti and Sachwald [48] , coopetition helps in saving organization’s research and development costs and achieving economies of scale. BarNir and Smith [49] asserted that coopetition helps firms take on stronger rivals and reach out to new markets. Other works concluded that coopetition is a better alternative to competing with each other [50] and that coopetition leads to risk sharing and making of secure contracts [51] by pooling the resources and benefiting from each other’s strengths. Uncertainty management and its eventual reduction is a key benefit of coopetition as well [52] . Thus given the significance of the concept of coopetition, it was relevant to study whether coopetition mediates the link between cultural intelligence and the intention to share knowledge. This is because that some people are at ease in different cultures, others find it a big challenge to deal with cultural diversity [53] . This is confirmed by the study of international work experience studied by scholars such as McCall and Hollenbeck [54] . These studies concluded that individuals who are open to new experiences are less biased [55] and are more accepting of the difference between cultures [56] .
The findings of this study suggest that motivation sub-construct in the cultural intelligence construct had the highest direct effect as an antecedent (β = 0.059****, t = 2.279), which supports hypothesis 1d. This was followed by the direct effect of the behavioral sub-construct in the cultural intelligence construct (β = 0.043****, t = 2.346), which supports hypothesis 1a. The study also found support for H1b and H1c. Thus, MAs need to be motivated and behaviorally oriented regarding cultural nuances to improve their intention to share their knowledge. The study also found support for hypothesis 2 which suggests that gender does not affect the knowledge sharing intentions.
This study makes three distinct and key contributions.
・ First, the research identified that coopetition mediates the relationship between cultural intelligence and the intention to share knowledge. Thus, intra organizational collaboration and competition as operationalized by the “coopetition” construct, needs to be closely monitored in the organizations for the design of effective management controls systems. This phenomenon is unique as coopetition involves both collaboration and completion at the same time amongst the MAs working in multinational firms. The reason to engage in coopetition could be competitive environmental factors or the nature of the work and however such reasons were not probed into. Further, this juxtaposition is analogous in finding common workable ground as evidenced by the ability of risk-taking managers meandering through rigid organizational controls to innovate [57] and the emerging market entrepreneurs using technology solutions for different operational needs such as mobile banking [58] . Thus, culturally intelligent MAs collaborate and compete at the same time, sharing knowledge for creating value for their firm (since the R square of both coopetition and the intention to share knowledge construct was high).
・ Second, the multi group analysis (MGA) revealed no significant gender related difference amongst the practicing management accountants. IPMA results suggest that gender is irrelevant in the intention to share knowledge. The findings of this study are consistent with the prior studies by Engle and Crowne [16] that gender does not play in role in CQ add to the work of Dragoni et al. [59] on managers overseas professional work experience.
・ Third, the study contributes to the methods by illustrating the modelling of the construct “cultural intelligence”, formatively and validating it by fsQCA. A key contribution of this paper is the modelling of cultural intelligence as a second order formative construct and thus this paper demonstrates the use of formative constructs in behavioral management accounting research. This is a key contribution to the methods literature.
The study has certain limitations as well, including the reliance on self-reported information by MAs. As per Ajzen [60] self-reports are quite accurate when the data collected is not of a highly sensitive nature. In this exploratory study, sensitive information was not gathered, which substantially increases the acceptability of the results. The second limitation is the sample size of 107. It should be noted here that collecting information from practicing MAs is highly time and resource consuming due to their busy schedule and their requirements for organizational clearance. However, future research may build on these findings and explore further insights in the emerging market context.
6. Conclusion
The study concluded that that coopetition did mediate the relationship between the cultural intelligence and the intention to share knowledge. It was also observed that MAs could be motivated and behaviorally oriented to enhance their intention to share knowledge.
Conflicts of Interest
The author declares no conflicts of interest regarding the publication of this paper.
Cite this paper
Varma, A. (2019) Do Culturally Intelligent Management Accountants Share More Knowledge?―The Mediating Role of Coopetition as Evident from PLS SEM and fsQCA. Theoretical Economics Letters, 9, 100-118. https://doi.org/10.4236/tel.2019.91009
ReferencesAng, S. and Van Dyne, L. (2008) Conceptualization of Cultural Intelligence: Definition, Distinctiveness, and Nomological Network. In: Ang, S. and Van Dyne, L., Eds., Handbook of Cultural Intelligence: Theory, Measurement, and Applications, M.E. Sharpe, New York, 3-15.Earley, P.C., Ang, S. and Tan, J. (2006) CQ: Developing Cultural Intelligence at Work. Stanford University Press, Palo Alto.Groves, K.S., Feyerherm, A. and Gu, M. (2015) Examining Cultural Intelligence and Cross Cultural Negotiation Effectiveness. Journal of Management Education, 39, 209-243. https://doi.org/10.1177/1052562914543273Varma, A. (2018) Big Data Usage Intention of Management Accountants: Blending the Utility Theory with the Theory of Planned Behavior in an Emerging Market Context. Theoretical Economics Letters, 8, 2803-2817.
https://doi.org/10.4236/tel.2018.813176Varma, A. and Sahoo, S. (2018) A Behavioral Economics Study on the Management Accountant’s Professional Networking Practices through Mobile Technologies. Theoretical Economics Letters, 8, 3092-3108.
https://doi.org/10.4236/tel.2018.814192Varma, A. (2018) Qualitative Evidence for a Behavioral Extension of the Expectancy Valence Theory: The Netflix-Twitter-Yakult Case. Theoretical Economics Letters, 8, 3457-3469. https://doi.org/10.4236/tel.2018.815212Crowne, K.A. (2008) What Leads to Cultural Intelligence? Business Horizons, 51, 391-399.Osland, J.S. and Osland, A. (2006) Expatriate Paradoxes and Cultural Involvement. International Studies of Management & Organization, 35, 91-114.
https://doi.org/10.1080/00208825.2005.11043740Tharapos, M., O’Connell, B., Dellaportas, S. and Basioudis, I. (2018) Are Accounting Academics Culturally Intelligent? An Empirical Investigation. The British Accounting Review, in Press. https://doi.org/10.1016/j.bar.2018.08.002Sahin, F., Gurbuz, S. and Koksal, O. (2014) Cultural Intelligence (CQ) in Action: The Effects of Personality and International Assignment on the Development of CQ. International Journal of Intercultural Relations, 39, 152-163.
https://doi.org/10.1016/j.ijintrel.2013.11.002Ang, S., Van Dyne, L., Koh, C., Ng, K.-Y., Templer, K.J., Tay, C. and Chandrasekar, N.A. (2007) Cultural Intelligence: Its Measurement and Effects on Cultural Judgment and Decision Making, Cultural Adaptation and Task Performance. Management and Organization Review, 3, 335-371.
https://doi.org/10.1111/j.1740-8784.2007.00082.xLin, Y.-C., Chen, A.S.-Y. and Song, Y.-C. (2012) Does Your Intelligence Help to Survive in a Foreign Jungle? The Effects of Cultural Intelligence and Emotional Intelligence on Cross Cultural Adjustment. International Journal of Intercultural Relations, 36, 541-552. https://doi.org/10.1016/j.ijintrel.2012.03.001Earley, P.C. and Ang, S. (2003) Cultural Intelligence: Individual Interactions across Cultures. Stanford University Press, Palo Alto, CA.Groves, K.S. and Feyerherm, A.E. (2011) Leader Cultural Intelligence in Context: Testing the Nmoderating Effects of Team Cultural Diversity on Leader and Team Performance. Group & Organization Management, 36, 535-566.
https://doi.org/10.1177/1059601111415664Ang, S., Van Dyne, L. and Koh, C. (2006) Personality Correlates of the Four-Factor Model of Cultural Intelligence. Group & Organization Management, 31, 100-123.
https://doi.org/10.1177/1059601105275267Engle, R.L. and Crowne, K.A. (2014) The Impact of International Experience on Cultural Intelligence: An Application of Contact Theory in a Structured Short-Term Program. Human Resource Development International, 17, 30-46.
https://doi.org/10.1080/13678868.2013.856206Nonaka, I. (1994) A Dynamic Theory of Organizational Knowledge Creation. Organization Science, 5, 14-36. https://doi.org/10.1287/orsc.5.1.14Sanchez, R. and Heene, A. (1996) Competence Perspectives on Strategic Learning and Knowledge Management. In: Heene, A. and Sanchez, R., Eds., Strategic Learning and Knowledge Management, Wiley & Sons, Chichester, 3-18.Hansen, M.T. (1999) The Search-Transfer Problem: The Role of Weak Ties in Sharing Knowledge across Organization Subunits. Administrative Science Quarterly, 44, 82-111. https://doi.org/10.2307/2667032Felício, J.A., Rodrigues, R. and Caldeirinha, V.R. (2012) The Effect of Intrapreneurship on Corporate Performance. Management Decision, 50, 1717-1738.
https://doi.org/10.1108/00251741211279567He, W. and Wei, K. (2009) What Drives Continued Knowledge Sharing? An Investigation of Knowledge-Contribution and Seeking Beliefs. Decision Support Systems, 46, 826-838. https://doi.org/10.1016/j.dss.2008.11.007Baskerville, R. (2017) Individual Information Systems as a Research Arena. European Journal of Information Systems, 20, 251-254.
https://doi.org/10.1057/ejis.2011.8Brazelton, J. and Gorry, A. (2003) Creating a Knowledge-Sharing Community: If You Build It, Will They Come? Communications of the ACM, 46, 23-25.
https://doi.org/10.1145/606272.606290Bouncken, R.B. and Fredrich, V. (2012) Coopetition: Performance Implications and Management Antecedents. International Journal of Innovation Management, 16, 1-12. https://doi.org/10.1142/S1363919612500284Bengtsson, M. and Kock, S. (2000) Coopetition in Business Networks to Cooperate and Compete Simultaneously. Industrial Marketing Management, 29, 411-426.
https://doi.org/10.1016/S0019-8501(99)00067-XBirnberg, J.G. and Snodgrass, C. (1988) Culture and Control: A Field Study. Accounting, Organizations and Society, 13, 447-464.
https://doi.org/10.1016/0361-3682(88)90016-5Chin W.W. ,et al. (1998)The Partial Least Squares Approach to Structural Equation Modeling Modern Methods for Business Research 295, 295-336.DeVellis, R.F. (2016) Scale Development: Theory and Applications. Vol. 26, Sage, Thousand Oaks.Puccino S. ,et al. (2007)Worldwide Practices and Trends in Expatriate Compensation and Benefits Benefits & Compensation Digest 44, 34-38.Podsakoff, P.M., MacKenzie, S.B., Lee, J.Y. and Podsakoff, N.P. (2003) Common Method Biases in Behavioral Research: A Critical Review of the Literature and Recommended Remedies. Journal of Applied Psychology, 88, 879.
https://doi.org/10.1037/0021-9010.88.5.879Hwang, Y., Lin, H. and Shin, D. (2018) Knowledge System Commitment and Knowledge Sharing Intention: The Role of Personal Information Management Motivation. International Journal of Information Management, 39, 220-227.
https://doi.org/10.1016/j.ijinfomgt.2017.12.009Chong, S. (2011) KM Implementation in a Public Sector Accounting Organization: An Empirical Investigation. Journal of Knowledge Management, 15, 497-512.
https://doi.org/10.1108/13673271111137457Lowry, P.B. and Gaskin, J. (2014) Partial Least Squares (PLS) Structural Equation Modeling (SEM) for Building and Testing Behavioral Causal Theory: When to Choose It and How to Use It. IEEE Transactions on Professional Communication, 57, 123-146. https://doi.org/10.1109/TPC.2014.2312452McIntosh, C.N., Edwards, J.R. and Antonakis, J. (2014) Reflections on Partial Least Squares Path Modeling. Organizational Research Methods, 17, 210-251.
https://doi.org/10.1177/1094428114529165Ringle, C.M., Wende, S. and Becker, J.M. (2015) SmartPLS 3. SmartPLS GmbH, Boenningstedt. http://www.smartpls.comGelfand, M.J., Imai, L. and Fehr, R. (2008) Thinking Intelligently about Cultural Intelligence: The Road Ahead. In: Ang, S. and Van Dyne, L., Eds., Handbook of Cultural Intelligence: Theory, Measurement, and Applications, M.E. Sharpe, New York, 375-387.Ali, M. and Park, K. (2016) The Mediating Role of an Innovative Culture in the Relationship between Absorptive Capacity and Technical and Non-Technical Innovation. Journal of Business Research, 69, 1669-1675.
https://doi.org/10.1016/j.jbusres.2015.10.036Duarte, P. and Amaro, S. (2018) Methods for Modelling Reflective-Formative Second Order Constructs in PLS: An Application to Online Travel Shopping. Journal of Hospitality and Tourism Technology, 9, 295-313.Becker, J.M., Klein, K. and Wetzels, M. (2012) Hierarchical Latent Variable Models in PLS-SEM: Guidelines for Using Reflective-Formative Type Models. Long Range Planning, 45, 359-394. https://doi.org/10.1016/j.lrp.2012.10.001Nunnally, J. (1978) Psychometric Methods. McGraw-Hill Book Co., New York.Fornell, C. and Larcker, D.F. (1981) Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. Journal of Marketing Research, 18, 39-50. https://doi.org/10.1177/002224378101800104Sarstedt, M., Ringle, C.M., Smith, D., Reams, R. and Hair, J.F. (2014) Partial Least Squares Structural Equation Modeling (PLS-SEM): A Useful Tool for Family Business Researchers. Journal of Family Business Strategy, 5, 105-115.
https://doi.org/10.1016/j.jfbs.2014.01.002Hair, J.F., Black, W.C., Babin, B.J., Anderson, R.E. and Tatham, R.L. (2006) Multivariate Data Analysis. Vol. 6, Pearson, London.Morris, M.G., Venkatesh, V. and Ackerman, P.L. (2005) Gender and Age Differences in Employee Decisions about New Technology: An Extension to the Theory of Planned Behavior. IEEE Transactions on Engineering Management, 52, 69-84.
https://doi.org/10.1109/TEM.2004.839967Ragin, C.C. (2008) Redesigning Social Inquiry: Fuzzy Sets and Beyond. University of Chicago Press, Chicago and London.
https://doi.org/10.7208/chicago/9780226702797.001.0001Fiss, P.C. (2011) Building Better Causal Theories: A Fuzzy Set Approach to Typologies in Organizational Research. Academy of Management Journal, 54, 393-420.
https://doi.org/10.5465/amj.2011.60263120Ganter, A. and Hecker, A. (2014) Configurational Paths to Organizational Innovation: Qualitative Comparative Analyses of Antecedents and Contingencies. Journal of Business Research, 67, 1285-1292. https://doi.org/10.1016/j.jbusres.2013.03.004Miotti, L. and Sachwald, F. (2003) Co-Operative R&D: Why and with Whom? An Integrated Framework of Analysis. Research Policy, 32, 1481-1499.
https://doi.org/10.1016/S0048-7333(02)00159-2BarNir, A. and Smith, K.A. (2002) Interfirm Alliances in the Small Business: The Role of Social Networks. Journal of Small Business Management, 40, 219-232.
https://doi.org/10.1111/1540-627X.00052Bougrain, F. and Haudeville, B. (2002) Innovation, Collaboration and SMEs Internal Research Capacities. Research Policy, 31, 735-747.
https://doi.org/10.1016/S0048-7333(01)00144-5Meyer, H. (1998) My Enemy, My Friend. Journal of Business Strategy, 19, 10-16.
https://doi.org/10.1108/eb039962Gnyawali, D.R. and Park, B.-J. (2009) Coopetition and Technological Innovation in Small and Medium-Sized Enterprises: A Multilevel Conceptual Model. Journal of Small Business Management, 47, 308-330.
https://doi.org/10.1111/j.1540-627X.2009.00273.xTeekens, H. (2003) The Requirement to Develop Specific Skills for Teaching in an International Setting. Journal of Studies in International Education, 7, 108-119.
https://doi.org/10.1177/1028315302250192McCall, M.W. and Hollenbeck, G.P. (2002) Developing Global Executives: The Lessons of International Experience. Harvard Business School Press, Boston.Flynn, F.J. (2005) Having an Open Mind: The Impact of Openness to Experience on Interracial Attitudes and Impression Formulation. Journal of Personality and Social Psychology, 88, 816-826. https://doi.org/10.1037/0022-3514.88.5.816Bhagat, R.S. and Prien, K.O. (1996) Cross-Cultural Training in Organizational Contexts. In: Landis, D. and Bhagat, R.S., Eds., Handbook of Intercultural Training, Sage, Thousand Oaks, 216-230.Varma, A., Bhalotia, K. and Gambhir, K. (2018) Innovating for Competitive Advantage: Managerial Risk-Taking Ability Counterbalances Management Controls. Journal of Management and Governance, 1-21.Varma, A. (2018) Mobile Banking Choices of Entrepreneurs: A Unified Theory of Acceptance and Use of Technology (UTAUT) Perspective. Theoretical Economics Letters, 8, 2921-2937. https://doi.org/10.4236/tel.2018.814183Dragoni, L., Tesluk, P.E., VanKatwyk, P., In-Sue, O., Moore, O.A. and Hazucha, J. (2014) Developing Leaders’ Strategic Thinking through Global Work Experience: The Moderating Role of Cultural Distance. Journal of Applied Psychology, 99, 867-882. https://doi.org/10.1037/a0036628Ajzen, I. (1991) The Theory of Planned Behavior. Organizational Behavior and Human Decision Processes, 50, 179-211.
https://doi.org/10.1016/0749-5978(91)90020-T