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ERM Scale Development and Validation in Indian IT Sector

Assistant Professor, Department of Management, BITS Pilani, Rajasthan, India
Postal Address: 6068-G, NAB, BITS Pilani, Pilani Campus, Rajasthan - 333031, India
Author's Organizational Website:
Email: [email protected]
Dr. Arun Kumar is an assistant professor in Department of Management, BITS Pilani.
His areas of interest are relationship marketing, consumer behavior and e-marketing.
Computer Science Student, Department of Management, BITS Pilani, Rajasthan, India
Postal Address: 6068-G, NAB, BITS Pilani, Pilani Campus, Rajasthan - 333031, India
Author's Organizational Website:
Email: [email protected]
Mr. Sri Harsha Yayi is a B.E. (Hons.), Computer Science student at BITS Pilani.
© Arun Kumar Agariya and Sri Harsha Yayi, 2015

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The research paper aims at developing a valid ERM (Employee Relationship Management) Scale in context of Indian IT sector. A standard methodology of scale development is used consisting of exploratory and confirmatory factor analysis. The findings clearly depicts that ERM in Indian IT sector is a multi-dimensional construct comprising of five factors namely communication and coordination; knowledge management; organizational policies; organizational environment and perceived trust. Although a plenty of literature is available in relationship marketing domain, still there are few studies done in context of employee relationship management. The novelty of this research work lies in developing and validating an instrument from employee perspectives which may serve as a diagnostic instrument for Indian IT sector. Academically this study bridges the gap in the literature by proposing an ERM scale, managerially this proposed scale will help the top management of the organization to focus on critical factors leading to ERM and thereby creating committed and motivated employees to foster a win-win situation by delighting customers and enhancing the profitability of the organization as a whole.


Employee relationship management; ERM scale; exploratory factor analysis; confirmatory factor analysis; Indian IT sector


With a paradigm shift in the global economy, Asia is anticipated to establish itself as the world’s economic leader. India together with China is to play an important role in transforming Asia to the pinnacle of economic prowess (BCG-CII report, 2013). The Indian Economy is set to grow at a faster rate in the next few years, the IT-sector being one among the significant catalysts. India’s IT-industry contributes to 7 per cent of the total global market share (Prasad et al., 2014). India’s information technology and information technology-enabled services (IT-ITeS) industry contributes for above 55 per cent of the total global sourcing market (excluding engineering services and R&D) in 2013 (Economic Survey, 2013-14) and the IT-BPM sector is estimated to reach US$ 135 billion in 2020.
In the global market, organizations ranging from conglomerate firms to government agencies have to put in a great deal of effort to survive and compete against their counterparts in the industry. According to Welbourne (2014) employee energy at work is a critical factor in assessing a firm’s growth, innovation and performance. It is of paramount importance that companies enhance their relationships with their employees as they are an indispensable asset to the firm, and it is with their dedication that such astounding growth in the IT sector has been achieved in recent years. Employee Relationship Management (ERM) is therefore an important organizational process that helps in better management of such employee – firm relations. A formal definition according to (Wargborn, 2008) Employee Relationship Management (ERM) is “... a strategic tool and a Human Resource Management process which focuses on the continuous perfection of the relationships between organizations and employees through increased communication and knowledge of individual and shared interests .”
In the light of recent advancement, organizations are emphasizing on finding the best practices for knowledge management, which is the essential information sharing process across the levels of organization for a better decision making (Jelenic, 2011) . Along with the growing realization in developing a strategic tool that assists employees, there is a concern for psychological health of them as well, and this is an issue that must be addressed. Empirical research on attrition rates and stress at work suggest that employees psychological health “.. should be an integral aspect of organizational commitment to its workforce.” (Machado et al., 2013). It is therefore evident that there is a need for Employee Relationship Management (ERM) within an organization operating in a competitive environment (Singh, 2011).


It is apparent from literature that the growth of a firm is dependent on the capabilities it possess and employment of resources that enhance the competitiveness of the business. There has been increased prominence in the concept of treating employees as internal customer to provide a better service quality to the external customers. Fisk et al. (1993) said the basic concept of internal marketing underlies in satisfying employees as internal customers which leads to satisfied external customers. A recent study in the Indian service sector reveals that employees are to be educated, motivated and satisfied to consistently deliver high service quality experience to external customers (Mishra, 2009).
Liao et al. (2004) emphasize that “Employee-employer and employee-organization relationships are part of a business’s internal relationship management.” According to (Kuzu and Ozilhan, 2014) the point of intersection of employee relations and employee performance is Employee Relationship Management. The concept of ERM has been derived from the concept and principles of CRM with technology-based relationship building from the customer to the employee domain. (Strohmeier, 2013).
In the literature, ERM is defined as a firm’s strategy on how to develop and maintain productive relationships with employees. To benefit this relationship a research made by Gillenson and Sanders (2005) suggests that ERM is a variation on the CRM theme, wherein web- based personalization techniques are used by a company to enhance the relationship with its employees.
According to Strohmeier (2013), there is no commonly accepted definition of ERM and from research it is revealed that there are other concepts that appear to be similar to the concept of ERM.A testimony to this is that in the past there has been a significant amount of research being undertaken on Human Capital Relationship Management (HRCM) by Rowe & Tucker (2006) suggesting that generic and one way employee relationships are being less effective with significant changes in the workforce. It is therefore necessary for organizations for developing solutions for effective management of employees.
The concept of Talent Relationship Management (TRM) by Katoen & Macioschek (2007) gives an insight on how to establish an active relationship with talented pool of employees on long term basis and in understanding TRM instruments of paramount importance that assist in developing this relationship. Empirical study by the same reveals that a good composition of TRM instruments lead to talented pool of employees and a positive perception towards the employer brand. For some time now, studies suggest there is a direct connection between investment in information technology (IT) and firm’s performance (Coltman et al., 2011). Some of them have suggested a positive relationship among them, while some others suggest the opposite (Weill, 1992). Bharadwaj (2000) said that effective and efficient use of IT resources is a key factor in assessing a firm’s performance from their counterparts. Boulding et al. (2005) have observed significant investment made by firms in developing Customer Relationship Management (CRM) systems. According to Bohling et al., (2006), these investments have been made by firms in information technology (IT) for an intelligent use of data and technology leading to a better management of knowledge about costumers.
On a closer look, the same concept is of limited applicability to small and medium enterprises with the shortcomings of available resources. Table-1 briefly lists the select list of studies done in employee’s context.
Table-1: Select List of Studies (2005-2013)
S.No. Author Context
1 Gillenson & Sanders (2005) The authors have applied the concept of web-based personalization techniques in context of US Navy sailors for their better satisfaction and retention.
2 Rowe & Tucker (2006) Human capital relationship management (HCRM) as a concept for establishing and developing strong employment relationship has been studied.
3 Katoen & Macioschek (2007) An empirical study on talent relationship management (TRM) instruments and employer branding in order to improve the organizational approach towards recruiting has been made.
4 Plakoyiannaki et al. (2008) Understanding the relationship between employee orientation and CRM success based on a case study by a firm in the UK automotive services sector.
5 Harer (2008) The existing practices in assessing employee satisfaction have been investigated and implications were assessing quality from employee’s perspective.
6 Mishra (2009) Internal marketing as a mechanism to motivate the employees and cultivate responsibility in order to enhance the quality across the organization has been proposed in the context of service organizations.
7 Tzafrir & Hareli (2009) Employee’s reaction to promotion and the conditions that led to certain reactions has been studied with the help of attribution theory of motivation and emotion.
8 Strohmeier (2013) An outline of the conceptual components of ERM is derived from the concept of customer relationship management (CRM) and implications were made.
9 Webster & Beehr (2013) Employee’s perception towards promotion decisions, its impact on performance has been studied and the necessity to study the outcomes of employees’ perception towards HRM practices.
10 Wu et al. (2013) An empirical study on the impact of internal marketing, job satisfaction and customer orientation on the productivity of an organization, interrelationships among the same have been studied in the context of Taiwan TFT-LCD manufacturing companies.
It is evident from the discussion above that a significant amount of research in relationship marketing has been focused on external relationship management in understanding the concepts of customer relationship marketing (CRM) to better serve the customers, supplier relationship management (SRM) to maximize the value of relationship with suppliers and channel partners (Liao et al., 2004; Gadde & Snehota, 2000; Agarwal & Singh, 2014a, 2014b) and the concept of internal marketing to train and motivate employees for a better service to the customers. But when employee relationship management (ERM) is concerned, there is no such study that has catered towards developing a comprehensive measure specifically in Indian context. Therefore this study specifically focuses on developing ERM scale as a strategic instrument specifically catering towards Indian IT sector


For this study, authors have initially developed 54 scale items derived from 67 research papers for identifying ERM constructs in Indian IT sector and 50 general relationship marketing scale items were taken from Agariya & Singh (2011) and those scale items were taken which are having the minimum of 5 citations; after this a total of 45 scale items were retained. Further to this depth interviews were conducted with the employees of Indian IT sector.
Depth interview
Depth interview was conducted with 17 employees of IT Companies (a representative sample of major IT Companies was the basis for selection) all across India. 30-45 minutes was the average duration of interview. List of dimensions (45) extracted from literature is given to employees along with an indicative definition of each dimension. This step has led to modification of questionnaire.
The authors provided a list of dimensions (45) obtained to the interviewees. They were asked to tick the ones based on the relevance. Their suggestions were also taken apart from the list of dimensions given, if any. After getting their responses the list was pruned to 32 based on modal values (10). Findings of depth interview shows, majority of the employees are aware of ERM practices. The major issues identified were related to infrastructure, organizational environment, information sharing, training and development and top management support.
Questionnaire survey
On the basis of final 32 dimensions the questionnaire was designed which was followed by a pilot survey to assess the content validity. From the result of the pilot survey 1 dimension are removed as a result, the revised questionnaire contained 31 dimensions (survey items). The revised questionnaire structure comprises of 2 major sections. First section was designed to gather the demographic profile of respondents whereas second section aims at measuring the respondent’s perceptions on ERM measures. A 5- point Likert-type scale (From 1= strongly disagree to 5= strongly agree) was used to indicate the perceptions of the employees.
Responses were received by using both the modes offline as well as online from the employees of IT companies all across India. In totality 270 responses were received. The data was divided in two equal parts, from first half exploratory analysis was carried out, whereas the second half was used to carry out the confirmatory factor analysis. The demographic profile of the respondents is given in Table-2.
Table-2: Demographic Profile of the Respondents (field survey)
S.No. Demographic Criteria Particulars %
1 Gender Male 75.6%
Female 24.4%
2 Age Between 18 -30 years 86%
Between 30-45 years 11.8%
Above 45 years 2.2%
3 Education Level Undergraduate 18.5%
Graduate 58.5%
Postgraduate and above 23%
4 Designation System engineers 31%
System managers 4%
System associate 25.6%
Project leaders 11.4%
System testers 28%
5 Monthly Salary Less than Rs. 30,000 45%
Rs. 30,000-40,000 13.3%
More than Rs. 40,000 41.7%
6 Employment duration in
current IT company
Less than 1 Years 36.2%
Between 1-3 Years 44.4%
More than 3 Years 19.4%


The reliability of the data is found 0.962, which is in the quite acceptable range (> 0.7) (Nunnally, 1978). Further to this KMO statistics was calculated that shows the value 0.913 (>0.5) which clearly falls in the acceptable range to carry out further analysis. In exploratory factor analysis, based on the results of rotated component matrix, 5 factors were emerged along with 26 indicators contributing towards 65.82% of the variance. On the basis of these factors ERM models were proposed. The extracted factors along with their indicators are shown in rotated component matrix (Table-3).
Table-3: Exploratory factor analysis (Rotated component matrix)
PET1         .769
ORE1       .565  
PET2         .658
KNM1 .616        
KNM2 .628        
KNM3 .571     .666  
COC1   .591      
COC2   .738      
COC3   .662      
COC4   .673      
COC5   .524      
PET3         .692
ORE2       .624  
ORP1     .693    
ORP2     .641    
COC6   .511      
KNM4 .708        
ORP3     .671    
PET4         .665
ORE3       .824  
ORP4     .730    
ORE4       .648  
PET5         .524
ORE5       .654  
ORP5     .702    
ORE6       .630  
The measurement model (Figure-1) is represented as a multi-dimensional construct explained by five factors resulted from exploratory factor analysis. This measurement model is verified by using the second half of the data (Sample size: 135).
Measurement model is accepted because of acceptable level of fit based on the calculated measures (Anderson & Gerbing, 1988). A total of 5 indicators namely COC4, ORP2, ORE1, ORE2 and PET1 were eliminated in this model because of poor loadings (<0.5). The calculated statistics of measurement model is shown in Table-4. In addition to this all the indicators loaded significantly on the corresponding latent constructs. The values of the fit indices indicate a reasonable fit of the measurement model with the sample data (Byrne, 2001).
Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. Rotation converged in 7 iterations. KNM: Knowledge Management, COC: Communication and Coordination, ORP: Organizational Policies, ORE: Organizational Environment, PET: Perceived Trust
Figure-1: Model 1- Measurement Model (5 Factor model)
Table-4: Calculated statistics for the models 1
S.No. Model Fit Absolute Measures Incrementalfit Measures Parsimoniousfit Measures RMSEA
χ2 χ2/df RMR GFI


Model 1 460.57 2.57 0.05 0.83


0.89 0.84 0.69 0.07
Table-5: Composite reliability of the constructs
Construct Composite Reliability
KNM 0.71
COC 0.67
ORP 0.63
ORE 0.83
PET 0.79
Table-5 above clearly indicates the calculated values of composite reliability for the five constructs and found more than 0.6, which is quite acceptable and also indicates the reliability of constructs (Carmines and Zeller, 1988). Construct validity is established in this study by establishing the content validity, convergent validity and discriminant validity. Content validity is verified through expert’s interaction and literature support in the area of ERM. Convergent validity is assessed by examining the AVE (average variance extracted and factor loadings (Fornell and Larcker, 1981). All the indicators have shown significant loadings onto their respective latent constructs with values varying in between 0.63 to 0.82. In addition, AVE for each construct is greater than or equal to 0.50, which further supports the convergent validity of the constructs. Discriminant validity was established by comparing the AVE values with the corresponding inter-construct squared correlation estimates. The comparison revealed AVE values are higher than the square of the inter-construct correlations. Thus, the measurement model reflects good construct validity and desirable psychometric properties (Agariya & Singh, 2013).
Figure-2: Model 2- Structural Model (5 Factor model)
In the second model (Figure-2), the structural ERM model is validated. The calculated statistics for the same is shown in Table-6. In short, the structural model confirms the five-factor structure of Employee relationship management.
Table-6: Calculated Statistics for Model-2
S.No. Model Fit   RMSEA
Absolute Measures Incrementalfit Measures Parsimoniousfit Measures
Model 3 473.46 2.57 0.05 0.91 0.88 0.93 0.87 0.73 0.05


The contribution of this study is to establish the important factors that explain ERM in Indian IT sector and are identified as communication and coordination, knowledge management, organizational policies, organizational environment and perceived trust. The factors along with sub-dimensions are explained below. These factors have to give utmost importance by Indian IT Companies so as to enhance the ultimate relationship with their customers and overall profitability.
Knowledge Management (KNM)
It is of at-most importance for every organization to efficiently manage information and knowledge gathered from internal and external sources. This factor is of important organizational relevance which assists managers, employees to simplify organizational activities, for effective and efficient decision making, to develop strategies for achieving organizational goals.
This factor includes dimensions such as technology infrastructure - updated technology infrastructure to maintain smooth flow of work process across different levels of organization; information database - a centralized database of all the information required for an efficient access for employees; role clarity - roles, responsibilities of different positions in the organization are clearly documented and shared with employees; feedback from employees - regular review and suggestions taken from employees on training programs, recent interventions across the organization.
Communication and Coordination (COC)
Effective communication is the cornerstone for developing and establishing employeeemployer relationship and coordinating activities across the organization. Promoting activities that enhance coordination among employees and with senior management enables open communication, strengthen employee motivation and trust.
The first factor communication and coordination has dimensions as transparency in information sharing - organization shares each and every aspect of important information with minute details with concerned employees; downward communication - senior management of an organization communicates effectively with every other employee of the organization; interdepartmental communication - communication and co-ordination between various departments across the organization for a better functioning of the organization as a whole; team building - activities that promote team spirit, prevent conflicts among employees and enhance trust among them, constructive feedback - regular performance feedback to employees for a better understanding of their roles and responsibilities in the organization.
Organization Policies (ORP)
Organizational Policies as a factor it includes dimensions as workplace bias - organization does not emphasize upon gender, native state bias; employee security - measures for protecting employees privacy, security and safety are taken by the organization; employee aspirations - goals, aspirations and values of employees are strongly considered by the organization; empathy - organization is actively interested in employee’s professional development and career advancement activities.
Organizational Environment (ORE)
Organizational environment impacts employee’s motivation to perform their task, health and work-life balance. So, it is necessary for organizations to create an organizational environment that positively impacts employee morale and productivity of organization.
Workplace environment as a factor it encompasses dimensions such as work motivation - if employees perceive their work as challenging, stimulating and rewarding; work-life balance - an environment that supports a balanced work-life of employees; flexibility - providing employees with an opportunity to choose where to work from, flexible timings and job autonomy; employee engagement - to promote a culture of freedom for employees to think, suggest and design interventions for the betterment of the organization as a whole.
Perceived Trust (PET)
Organizational trust is important for any organization, which underlies effective employee-employer relationship, impact on employee behavior, in retaining talented pool of employees which significantly contribute for overall organizational performance.
This factor comprises of dimensions such as job satisfaction - if an employee is satisfied with one’s roles, responsibilities and work position; organizational justice - it is the employee perception of fairness in all aspects related to employees in an organization; organizational support - it is the perception of employees if they can rely on their senior management in critical conditions; turnover - if employees strongly trust their senior management they will not seek other employment opportunities , decreasing the turnover rate.
Although a plethora of literature is available in area of relationship marketing, like customer, supplier and partner relationship management but only a handful of studies found in context of ERM specifically catering to Indian service sector, which clearly depicts a lacuna from the perspective of holistic marketing orientation. This study bridges this gap in the academic literature by proposing an instrument termed as ERM scale specifically catering to Indian IT Sector. Managerially it will help the top management in identifying the major areas of concern from employee’s perspective and implementing the best practices so as to enhance the employee morale and commitment, reduced employee turnover, which in turn will lead to higher customer satisfaction level that will ultimately lead to better profitability and a win-win situation for all the stakeholders.
That will also lead to better image of IT Company in the market place in the minds of prospective employees. Apart from this it will also have a positive impact on Indian economy because of the contribution of IT sector in Indian GDP.


The major limitations of this research work is in terms of the sample size, a large and more diversified sample can lead to a better snapshot of ERM in Indian IT sector. Also the generalizability of the proposed scale can also be tested in different business and national context.


Authors want to acknowledge Prof. Deepali Singh, Professor, ABV-IIITM, Gwalior and Dr. Jyoti, Assistant Professor, BITS Pilani for giving directions and valuable insights during the work.


Agariya, A. K., & Singh, D. (2011). What really defines relationship marketing? A reviewof definitions and general and sector-specific defining constructs. Journal ofRelationship Marketing, 10(4), 203-237.

Agariya, A. K., & Singh, D. (2013).CRM Scale Development and Validation in IndianPublic Hospitals. Journal of Health Management, 15(2), 275-291.

Agarwal, A., & Singh, D. (2014a). PRM index: an innovative tool for measuring partnerrelational aspects in Indian automobile sector. International Journal of ValueChain Management, 7(2), 171-189.

Agarwal, A., & Singh, D. (2014b). Partner Relationship Management (PRM) Index: AnInnovative Approach For Enhancing Channel Partner Relationships. Journal ofInternet Banking and Commerce, 19(1).

Anderson, J. C., &Gerbing, D. W. (1988). Structural equation modeling in practice: Areview and recommended two-step approach. Psychological bulletin, 103(3),411.

BCG-CII report (2013), IT for India- New Horizons, New Opportunities accessed from, (accessed on 24th October, 2014).

Bharadwaj, A. S. (2000). A resource-based perspective on information technologycapability and firm performance: an empirical investigation. MIS quarterly, 169-196.

Bohling, T., Bowman, D., LaValle, S., Mittal, V., Narayandas, D., Ramani, G., &Varadarajan, R. (2006).CRM Implementation Effectiveness Issues and Insights.Journal of Service Research, 9(2), 184-194.

Boulding, W., Staelin, R., Ehret, M., & Johnston, W. J. (2005). A customer relationshipmanagement roadmap: what is known, potential pitfalls, and where to go. Journalof Marketing, 69(4), 155-166.

Byrne, B.M. (2001). Structural Equation Modeling with AMOS: Basic Concepts,Applications and Programming, Lawrence Erlbaum Associates, Mahwah, NJ.

Carmines, E.G. and Zeller, R.A. (1988).Reliability and Validity Assessment.Sage,Beverly Hills, CA.
Coltman, T., Devinney, T. M., &Midgley, D. F. (2011).Customer relationshipmanagement and firm performance. Journal of Information Technology, 26(3),205-219.

Economic Survey (2013-14), Service Sector accessed from, (accessed on 24th October,2014).

Fisk, R. P., Brown, S. W., &Bitner, M. J. (1993).Tracking the evolution of the servicesmarketing literature. Journal of Retailing, 69(1), 61-103.

Fornell, C., &Larcker, D. F. (1981).Evaluating structural equation models with unobservable variables and measurement error.Journal of marketing research,39-50.

Gadde, L. E., &Snehota, I. (2000).Making the most of supplier relationships.IndustrialMarketing Management, 29(4), 305-316.

Gillenson, M. L., & Sanders, T. C. (2005). Employee relationship management: Applyingthe concept of personalization to US Navy sailors. Information systemsmanagement, 22(1), 45-50.

Harer, J. B. (2008). Employees as customers judging quality: enhancing employeeassessment. New Library World, 109(7/8), 307-320.

Jelenic, D. (2011). The importance of knowledge management in Organizations– withemphasis on the balanced scorecard learning and growth Perspective.InManagement, Knowledge and Learning, International Conference.

Katoen, R. J., &Macioschek, A. (2007).Employer Branding and Talent-Relationship-Management–Improving the Organizational Recruitment Approach.RetrievedSeptember, 23, 2011.
Kuzu, Ö. H., &Özilhan, D. (2014). The effect of employee relationships and knowledgesharing on employees’ performance: An empirical research on service industry.Procedia-Social and Behavioral Sciences, 109, 1370-1374.

Liao, S. H., Chang, J. C., Cheng, S. C., &Kuo, C. M. (2004). Employee relationship andknowledge sharing: A case study of a Taiwanese finance and securities firm.Knowledge Management Research & Practice, 2(1), 24-34.

Machado, T., Sathyanarayanan, V., Bhola, P., &Kamath, K. (2013). Psychologicalvulnerability, burnout, and coping among employees of a business processoutsourcing organization. Industrial psychiatry journal, 22(1), 26.

Mishra, S. (2009).Internal Marketing-A Tool to Harness Employees’Power in ServiceOrganizations in India. International Journal of Business and Management, 5(1),P185.

Nunnally, J. C. (1978). Psychometric theory. 2nd edition Tata McGraw-Hill: New York.

Plakoyiannaki, E., Tzokas, N., Dimitratos, P., &Saren, M. (2008). How critical isemployee orientation for customer relationship management? Insights from acase study. Journal of Management Studies, 45(2), 268-293.

Prasad, H. A. C., Sathish, R., & Singh, S. S. (2014).Emerging Global EconomicSituation: Opportunities and Policy Issues for Service Sector.

Rowe, K ., & Tucker, E . (2006).Human capital relationship management.Using CRMto customize employee relationships.Gandossy, R., Verma, N., & Tucker, E.(Eds.). (2006). Workforce wake-up call: Your workforce is changing, are you.John Wiley & Sons.

Singh, P. N., & Singh, P. N. (2011).Employee Relations Management.PearsonEducation India.

Strohmeier, S. (2013).Employee relationship management-Realizing competitiveadvantage through information technology? Human Resource ManagementReview, 23(1), 93-104.

Tzafrir, S. S., &Hareli, S. (2009). Employees' emotional reactions to promotiondecisions: The role of causal attributions and perceptions of justice. CareerDevelopment International, 14(4), 351-371.

Wargborn, C. (2008)Managing motivation in organizations. Why employee relationshipmanagement matters.

Webster, J. R., &Beehr, T. A. (2013).Antecedents and outcomes of employeeperceptions of intraorganizational mobility channels. Journal of OrganizationalBehavior, 34(7), 919-941.

Weill, P. (1992). The relationship between investment in information technology and firmperformance: a study of the valve manufacturing sector. Information SystemsResearch, 3(4), 307-333.

Welbourne, T. M. (2014). Two numbers for growth, innovation and high performance:Working and optimal employee energy. Organizational Dynamics.

Wu, W. Y., Tsai, C. C., & Fu, C. S. (2013). The Relationships among Internal Marketing,Job Satisfaction, Relationship Marketing, Customer Orientation, andOrganizational Performance: An Empirical Study of TFT/LCD Companies inTaiwan. Human Factors and Ergonomics in Manufacturing & Service Industries,
23(5), 436-449.