M15 - IT ManagementReturn

Logistics concepts are becoming less functional nowadays. The successful concept of just-in-time manufacturing seems untenable for 21st-century Europe. New ideas and new practices are emerging. One of the major trends in contemporary logistics is the demand-driven enterprise. Managing supply, fields and other processes in a company based on demand requires accurate demand forecasting at the relevant time. Relevant data are necessary for this forecasting. In the time of big data, the problem is not collecting data but evaluating them correctly. Data analytics is of great interest in business. The aim of the paper is to verify the possibilities of demand forecasting using traditional statistical methods (exponential smoothing, ARIMA), more advanced statistical methods (TBATS, etc.), methods based on artificial neural networks and a hybrid method. This is in conjunction with thorough data preparation, especially data normality testing. My research question is to provide, on data that contain a number of outliers, the results and the accuracy of the models when the data are or are not normalized. Demand forecasting for poetry books was chosen for the case study. The data were obtained from Google Trends data, i.e., searches for the topic of poetry for the period from 1 September 2013 to 31 September 2023. The results showed that the selected data contain a number of outliers that recur at regular intervals and are the result of a logical order of demand. The expected result was that data normalization increases the accuracy of the model. A method based on artificial neural networks provided significantly more accurate results. However, the resulting estimated underlying trend remained very similar. The article thus opens a discussion about the necessity of excluding outlying observations in time series where outliers exist at regular intervals.
Implications for Central European audience: The article poses fundamental scientific questions for Central Europe. Logistics concepts are developing rapidly in this area and Europe is the creator of significant innovations. Europe is currently facing great competition from foreign companies and new logistics concepts are becoming a necessity. Therefore, many European companies now feel the need to change their logistics processes. One of them may be to switch to an adaptive enterprise based on demand. The practical implications are also based on data from Europe.

Compliance costs are significant, and data related regulations are more frequent. The study argues if compliance spending can also generate additional value, as just a minimal regulation requirements fulfilment is not by any means achieving a competitive advantage. To test the hypotheses, a quantitative method with Structural Equation Modelling and Partial Least Squares (PLS) in the SmartPLS tool is used. The empirical data is collected from 98 data management professionals involved in recent European Union and General Data Protection Regulation (EU GDPR) projects associated with party data in larger organizations across Europe. The study suggests that Data Governance Span (DGS) leads to the increase of both data compliance related variables - Data Compliance Innovation (DCI) and Privacy Project Efficiency (PPE) - at the same time. However, its effect on the increase of Data Compliance Innovation (DCI) is weaker than the effect on the increase of Privacy Project Efficiency (PPE). Customer-Centric Orientation (CCO) is discovered to be an underlying mechanism of the relationship between Data Governance Span (DGS) and Data Compliance Innovation (DCI).
Implications for Central European audience: Firms in Central and Eastern Europe (CEE) did not use innovation enough in data compliance. DCI is the lowest in the CEE region DGS1 is the second lowest in CEE compared to all-regions-average. DGS1 refers to the business stakeholder involvement in the formal engagement, which assumes their responsibility.

COBIT is a process-oriented IT governance framework. In the 2019 version, the framework offers a significantly redesigned approach to prioritise processes and set process target capability levels. The design phase is very important to achieve a governance system in future. Although there are several design factors defined in the design phase of COBIT 2019, these factors do not assess process suitability and value for the governance system. Thus, connections and continuity among processes are not taken into consideration enough. Therefore, the aim of the article is to suggest another design factor based on the interrelationships of processes in the COBIT framework represented by its information flows. The nature of the proposed innovation is described, and the analysis of process information flows and items is performed. The article also publishes several inconsistencies in COBIT 2019 documentation that have been identified in the process of research. The application of process information flows and items analysis has been illustrated in two case studies. We have identified new information that can be relevant to decision making in the design phase and discussed their importance for the planned governance system. The results could help to improve the quality of the design phase by providing additional information about the context of the processes designed to ensure the governance system.
Implications for Central European audience: The implications for senior managers in the Central European region will be beneficial. Optimisation and effective use of information technologies is a prerequisite for achieving long-term competitiveness. COBIT is a best practice framework, and its implementation in companies is largely based on the specifics of each organisation. Therefore, it is important to pay close attention to the implementation phase of the application of COBIT. Framework application positively supports the holistic approach to management, resource optimisation, management based on responsibility and measurability. Today, these attributes of the organisation’s management are emphasised not only in Central Europe but in developed countries in general.

The article concerns the analysis of elements building the reliability of IT solutions used in the organizations (system reliability, usage reliability, information reliability and support service reliability) and their influence on IT performance in conditions of the crisis, which calls for social-distancing and forces employees to work remotely, putting IT performance at the centre of attention for organizations seeking ways to survive the crisis. The article aims at verifying the IT Reliability Model under such conditions and identifies which elements building the reliability of IT solutions may contribute to ensuring IT performance. The empirical study is performed among 115 organizations operating in Italy during the COVID-19 epidemic crisis in March 2020 (during the lockdown and peak of the epidemic). The results are compared with a previous study performed among 349 organizations from Poland and 288 organizations operating in Switzerland operating under normal conditions in January 2019. The obtained results confirmed that there are major differences in the strength and significance of the influence of four elements building IT reliability on IT performance among employees from organizations working under normal conditions and conditions of epidemical crisis. The usage reliability and support service reliability were proven to become key factors influencing IT performance under such critical conditions.
Implications for Central European audience: Central Europe was hit by the COVID-19 pandemic, and most of the organizations experienced problems with their functioning due to the need to establish new ways of working in a world of social distancing rules. Information technology became an especially important factor allowing them to remain continuity. Therefore, the analysis of factors influencing its performance during the crisis may help contemporary organizations in Central Europe to overcome the crisis caused by the sudden need to relay, more than ever, on information technology.

Theroretically, servitization benefits industrial companies to generate more revenue, integrate themselves deeper into the value chains of their customers and improves the competitiveness. The ongoing digital transformation can enable servitization towards more advanced services with a more customer centric view. Macro economically, the industrial sector is very important for most of the developed countries. The digital transformation is posing a triple challenge to the machining and equipment manufacturers and will require a continued development of the existing business models, a change of organizational structures and a strong leadership to remain successful. The companies will need to re-evaluate their market justification and define their value proposition to both existing and potentially new customers. New skills are required as data and analytics, represented by IIoT and AI, will play an ever-larger role in the companies’ interaction with their present and new customers. For the industrial companies, servitization is both linked to higher risk and to a higher earnings potential.
Implications for Central European audience: The implications for Central European industrial companies of the ongoing digitalisation and servitization will be profound. The European car industry is undergoing significant changes and not only due to E-mobility. Also Products-as-Service will have an impact on their whole value chain. The industrial sector in general and the machining industry in particular will need to re-assess its business models and revenue generation. In addition, senior management is already confronted with the need for both new skill-sets and possibly more agile organisational structures, where the industrial mind-set will be challenged by new service models and the thinking of the digital natives.

In recent years, artificial intelligence (AI) has become an emerging trend in different fields: science, business, medicine, automotive and education. AI has also reached marketing. The aim of the paper is to research how deeply AI is applied in marketing and what implications there are for marketing practitioners. Authors stated two research questions - which areas of AI are used in marketing and what implications AI delivers for marketing managers. To answer those questions, the authors conducted research on secondary data with AI examples used for marketing purpose. The analysis of gathered examples shows that AI is widely introduced into the marketing field, though the applications are at the operational level. This may be the effect of careful implementation of the new technology, still at the level of experimenting with it. The uncertainty of the outcome of AI implementation may affect the caution in putting these innovations into practice as well. Gathered examples proved that AI influences all aspects of marketing mix impacting both consumer value delivery as well as the marketing organization and management. The paper delivers implications for business, especially ideas about implementing AI into marketing, designing innovations and the ideas on how to incorporate new skills into marketing team required by the new technology.

The study examines the relationship between the governance program teams, business user participation, and innovation in data compliance projects. Many firms continue to struggle with their governance programs as its effective implementation requires organizational change and a higher rate of involvement of those with significant knowledge of the context of the system use. Leadership elements are observed in governance teams and the way how these elements impact both, participation and innovation in recent General Data Protection Regulation (GDPR) data compliance efforts. To test the hypotheses, a quantitative method with Structural Equation Modelling and Partial Least Squares (PLS) in SmartPLS tool are used. The empirical data are collected from 98 data management professionals involved in projects associated with customers’ data in larger organizations across European Union (EU). Research findings show that Governance Team Leadership (GTL) influence positively Line-of-Business Stakeholders Participation (LOBSP) and LOBSP influence positively Data Compliance Innovation (DCI) in GDPR efforts. Moreover, it shows that LOBSP is the underlying mechanism (mediator) of the relationship GTL and DCI. Data governance transfers data and information management towards managerial functions and strategic management. Data has become embedded within nearly every department and business unit, and its proper enterprise-wide governance requires much more rigorous alignment with business users and formation of one cross-functional unit – data stewardship team of proactive leaders. In opportunities and restrictions of data revolution underway, evidence of any sustainable organizational practices leading to innovations and competitive advantage is beneficial.

The paper concerns the notion of information technology (IT) reliability in an organization and User Experience as one of the factors which may potentially increase this reliability through a role of users (who should willingly use IT to perform tasks it is designed to support). Frequency of IT use (also in the context of economic advancement as a comparison between central Europe and North America) and job characteristics, such as task complexity, structuration and uniqueness are discussed as potential moderators strengthening that relation. The empirical research was performed among 550 organizations operating in Poland and USA in order to verify whether User Experience might be the factor positively influencing IT reliability in an organization and whether identified job characteristics indeed are strengthening that influence. The obtained results confirmed, among others, that the more complex and less routine are the tasks performed by the employee, the more significant is the influence of IT User Experience on IT reliability.