Contributions to Practice

The derived measures of this section show that knowing the employee’s drivers and inhibitors of using an enterprise information system helps to successfully implement those solutions.

Companies have to deal with the fact that REIS are enterprise information systems that need a planned and employee targeted rollout. Employees want to be involved in the implementation phase and want to have the feeling that the goals of the company, to implement REIS, are transparent. Moreover, employees need the feeling that their employer takes the implementation serious and that even the senior management is convinced of the mutual benefit of such systems. All stakeholders have to support and promote the solution. Otherwise, employees perceive missing additional value and potential fear from disclosure.

Companies should engage in transparent communication to prevent technological framing of the employee. If employees do not understand the implementation purpose, they start to interpret the purpose, which might lead to a negative frame. Therefore, transparent and comprehensible goal communication from the senior management to the workforce is recommended. The senior management is a key stakeholder. If REIS is only implemented and rolled out by the responsible line-of-business department (e.g., HR department), employees might perceive the solutions as a ‘personal toy’ of that specific department and do not see the overall business value. This transparent communication should be personal and verbal. However, this direct communication should be supported by blogging, e-mails, or poster campaigns. Raising awareness about the REIS solution and the holistic support of the management is evident for employee’s willingness to access and use the system. Furthermore, the direct management also plays a key role in the implementation process of REIS. For employees, the direct management often represents the company and its perspective. Therefore, if direct managers are not convinced of the benefit of such a solution, employees might not understand the value of such solutions at all. It was shown that the disclosure behavior of teams, where the direct manager supported the solution, was way higher than from other teams. Involvement and support of the direct management is evident for REIS success. Moreover, companies should communicate results of the usage of REIS. For instance, if an HR-Feedback system is introduced, the management should communicate results and insights as soon as possible. This helps to show the benefit of the solution and furthermore, strengthens the belief that the company communicates open and transparent. When employees contribute with sensitive information, they expect a benefit from it. Be it a personal or more global benefit. Companies should convince employees that their sensitive information disclosure contributes to a global purpose of the company and that employees can contribute to a positive change.

Furthermore, if similar solutions are already implemented in an organization, companies should either show the link between the different solutions or should communicate that the introduced REIS is the system that makes the difference. This study illustrated the challenges coming along with the application of two similar solutions at the same time. Employees were confused how these two approaches fit and link together. They did not see a meaning in using both solutions. Therefore, employees decided to use the well-known, old solution. As a countermeasure, results of both solutions should be integrated into one report and presented to the workforce.

Even though the derived measures of this section focused on the improvement of the disclosure intention of employees, the study also shows that it is important to take action regarding possible resistance against the system. As already found out in the previous section, passive and active resistance can lead to serious problems for REIS implementation. Employees could badmouth against the solution and therefore might establish a social norm of not using the system. Companies have to consider the fact that PIBV is a significant influencing factor that should be managed properly. Managing PIBV, however, is a long-term task. It relates to the employer- employee relationship, as well as technological characteristics of the solution. Especially managing the employer-employee relationship involves for example measures regarding organizational culture, trust relationship, and expectation management. Building a trustworthy culture, where everyone can speak up and is not feared of opportunism, is a costly and lengthy process (Galford and Drapeau 2003). However, on the long-term, these measures do not only support the rollout and implementation of REIS but as well might contribute to business success in general.

As shown in this study, several countermeasures can be derived from the model, to prevent non- usage of REIS. Companies should focus on a proper planned introduction of REIS solutions. If there are any concerns regarding the trust relationship between the workforce and the employer, early countermeasures should be conducted. A transparent and personal communication is a good starting point.

6.6.2. Limitations and Further Research

The present practical study has several limitations that should be considered. First, the data collection was conducted with a survey, which was not scientifically evaluated. Even though the underlying PIBV model is based on the evaluated and operationalized model of the previous section, the survey for data collection of this section was narrowed down due to practical aspects. Therefore, no implications for theory were given in this section. However, the model and the derived measures help to gain insights on the applicability of the questionnaire in practice and how it can support REIS implementation.

Second, this study was conducted in only one company. This was necessary, as the rollout process of the REIS was conducted in this specific company. However, one data source always implies the possibility of distortion according to a Common Method Bias (MacKenzie et al. 2011; Podsakoff et al. 2012). Although several measures were applied to prevent a bias (described in Section 5.6.1 and Section 6.3.2), the use of different sources or a temporal distribution of the data collection would additionally help to prevent biases. Furthermore, with regard to biased answering, it would help to decouple the survey completely from the company, as the factors related to the employer-employee relationship still represent critical questions for employees. Even though the insights and findings from the previous section were taken seriously and the design of the survey and introduction mail was changed, to prevent the impression that the company would have access to the data, employees still knew that ‘People Involvement’ was built in-house and therefore, also the survey was conducted by people within the company. For a

subsequent study, an independent company should be tested, where the REIS, as well as the PIBV survey, are not build or conducted in-house. This could furthermore help to prevent biased answering for sensitive questions.

Fourth, the amount of collected data (n=56) is on the bottom line of acceptable data points for a PLS analysis (see Section 6.3.1). The PLS method requires that the number of observations should be at least ten times the number of independent variables that affect the dependent variable with the most influencing factors. In this study, PIBV is the construct with the most items (five items) and has five influencing factors (see Figure 16). Therefore, the minimum amount of observations, with regard to this criterion, would be n=50. Another criterion is that the sample size should be at least ten times larger than the largest amount of indicators of a latent variable (Homburg and Klarmann 2006). With regard to the present model, also PIBV represents the construct with the most items (five items). With regard to this recommendation, the minimum amount of data points also should not be less than 50. Collecting more information would potentially help to increase the validity of this study for theory.

Fifth, the data collection was conducted after two weeks of each rollout phase. After approximately two months of the first rollout phase, the actual usage state was analyzed, and appropriate measures were derived. For an even more reliable and valid outcome of this practical study, a second evaluation of the usage and disclosure intention of employees would be helpful. It would help to show if the derived measures did really contribute to the employee’s usage intention of the REIS.