rss_2.0Engineering Management in Production and Services FeedSciendo RSS Feed for Engineering Management in Production and Serviceshttps://sciendo.com/journal/EMJhttps://www.sciendo.comEngineering Management in Production and Services Feedhttps://sciendo-parsed.s3.eu-central-1.amazonaws.com/6471bf48215d2f6c89daf931/cover-image.jpghttps://sciendo.com/journal/EMJ140216Investigation into the Key Barriers to Achieving UK “Construction 2025” Strategy Targetshttps://sciendo.com/article/10.2478/emj-2023-0032<abstract> <title style='display:none'>Abstract</title> <p>The “Construction 2025” is a United Kingdom (UK) Government Strategy introduced in 2013 to improve the construction industry in the United Kingdom by meeting outlined performance targets by 2025. However, with only a few years left to reach the targets, it is unclear how much industry is advancing to meet them. This paper reviews the progress to achieve the Strategy targets. The data collected from 96 UK construction professionals was utilised to assess the key barriers to achieving the UK “Construction 2025” Strategy targets. Results indicate that industry professionals are uncertain about reaching the reduction in overall cost and time targets by 2025. However, they are more positive about reducing greenhouse gas emissions and the trade gap. In terms of the key barriers, the results revealed a reluctance to adopt change, lack of implementation of new technology, fragmentation in the industry, and failure to adopt modern construction methods as the key barriers to the Strategy targets. The research is the first attempt at a comprehensive assessment of the progress and barriers to the UK “Construction 2025” Strategy. The results reinforce the call for government initiatives to transform the industry.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/emj-2023-00322023-12-29T00:00:00.000+00:00Artificial Intelligence in the Smart City — A Literature Reviewhttps://sciendo.com/article/10.2478/emj-2023-0028<abstract> <title style='display:none'>Abstract</title> <p>The influence of artificial intelligence (AI) in smart cities has resulted in enhanced efficiency, accessibility, and improved quality of life. However, this integration has brought forth new challenges, particularly concerning data security and privacy due to the widespread use of Internet of Things (IoT) technologies. The article aims to provide a classification of scientific research relating to artificial intelligence in smart city issues and to identify emerging directions of future research. A systematic literature review based on bibliometric analysis of Scopus and Web of Science databases was conducted for the study. Research query included TITLE-ABS-KEY (“smart city” AND “artificial intelligence”) in the case of Scopus and TS = (“smart city” AND “artificial intelligence”) in the case of the Web of Sciences database. For the purpose of the analysis, 3101 publication records were qualified. Based on bibliometric analysis, seven research areas were identified: safety, living, energy, mobility, health, pollution, and industry. Urban mobility has seen significant innovations through AI applications, such as autonomous vehicles (AVs), electric vehicles (EVs), and unmanned aerial vehicles (UAVs), yet security concerns persist, necessitating further research in this area. AI’s impact extends to energy management and sustainability practices, demanding standardised regulations to guide future research in renewable energy adoption and developing integrated local energy systems. Additionally, AI’s applications in health, environmental management, and the industrial sector require further investigation to address data handling, privacy, security, and societal implications, ensuring responsible and sustainable digitisation in smart cities.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/emj-2023-00282023-12-29T00:00:00.000+00:00Reshoring and Friendshoring as Factors in Changing the Geography of International Supply Chainshttps://sciendo.com/article/10.2478/emj-2023-0026<abstract> <title style='display:none'>Abstract</title> <p>The text covers the projection of the potential impact of the currently observed processes in the world economy on the international supply chains’ geography. The economic effects of the pandemic, the modern trade war and Russia’s aggression towards Ukraine are considered key factors in changing this geography. When examining the importance of these factors, the matrix of three components of global supply chains is adopted: production centres, transport corridors and consumption centres. The reasoning allowed for rejecting both the scenario of maintaining the so-called hyper-globalisation and forming a bilateral system of two isolated and hostile economic systems. The presented arguments lead to the expectation of a mixed solution in the form of the simultaneous existence of a system of high globalisation and concentrated regional systems. The primary objective of this study is to identify and assess emerging trends in the configuration of international supply chains. On this basis, it is also intended to identify the most likely scenario for the future formation of the geography of international supply chains. The research used the literature study methodology and deductive inference of the consequences of the identified processes taken as premises for reasoning. The above-presented arguments lead to the assumption that the so-called hyper-globalisation is probably unsustainable. Various economic, political, technological and social factors make it impossible to sustain, let alone further develop, the current logic of shaping the global economic system. A world economy system with a hybrid structure is expected to emerge. The model of full globalisation will coexist with the model of a multilateral structure with a regional character centred around the main consumption and production centres. The factors determining the evolution of economic globalisation have been systematised. Their potential impact is described, and a likely scenario for change is presented. The achieved results can contribute to the design of economic policy at the level of individual countries and their groupings.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/emj-2023-00262023-12-29T00:00:00.000+00:00Impact of Human Energy Expenditure on Order Picking Productivity: A Monte Carlo Simulation Study in a Zone Picking Systemhttps://sciendo.com/article/10.2478/emj-2023-0025<abstract> <title style='display:none'>Abstract</title> <p>This article aims to investigate the impact of allowable human energy expenditure (HEE) of order pickers on the throughput of workers in manual order zone picking systems MOP. The method used in this research is the Monte Carlo simulation, used while considering many human and job factors. The results showed that a worker’s gender and an item’s weight have little effect on the HEE. On the other hand, body weight, walking speed, distance travelled, and the targeted zone significantly impacted the HEE, rest allowance, and throughput. For example, male pickers at a weight of 75 kg can move up to speed to 1 m/s and pick up items weighing up to 5 kg without reaching the allowable HEE rate, equal to 4.3 kcal/min, and, thus, no rest is needed. Female pickers at a weight of 75 kg reach the allowable HEE rate, equal to 2.6 kcal/min, at a very low speed of approximately 0.1 m/s when picking up items up to 5 kg, and, thus, frequent rest is needed, which leads to low throughput. To increase the throughput of female pickers, they can be assigned to pick up lighter items. Utilising Monte Carlo simulation to evaluate the HEE in MOP while considering many factors.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/emj-2023-00252023-12-29T00:00:00.000+00:00Towards Integration of Business Process Management and Knowledge Management. IT Systems’ Perspectivehttps://sciendo.com/article/10.2478/emj-2023-0027<abstract> <title style='display:none'>Abstract</title> <p>The processes of globalisation, the ongoing threat of the COVID-19 epidemic, the continuing war in Ukraine, and constantly emerging new technological solutions require organisations to adapt to changes constantly. Meanwhile, implemented business process management (BPM) often fails to integrate processes and knowledge resources. The awareness of the IT systems’ role in management processes is still lacking. These premises influenced the implementation of the main research goal to identify the approach of Polish private and public enterprises and various industries to the BPM integration with knowledge management (MK) in the context of using new information technologies. The presented research results justify the usefulness of building relationships between the process and knowledge resources under dynamically changing conditions using IT systems. The diagnostic survey results confirmed the key importance of developing such BPM and MK elements as evidence-based decisions, strategic goals, measurement systems, databases, digital innovations, and IT use for data processing. The presented material can support managers of various organisation types in decision-making processes by fully understanding the IT systems’ role and potential in process and knowledge management. Also, the article’s implications are a source of guidelines, helping organisations to implement management systems based on modern technologies. The value of the publication is a wide range of respondents: 107 large, medium, small, and micro-enterprises operating in Poland. The article’s research results also concern economic activities such as production, logistics, transport, banking, insurance, IT, telecommunications/ media, public administration, healthcare/pharmaceuticals, consulting, energy, and construction.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/emj-2023-00272023-12-29T00:00:00.000+00:00Hierarchical Risk Communication Management Framework for Construction Projectshttps://sciendo.com/article/10.2478/emj-2023-0031<abstract> <title style='display:none'>Abstract</title> <p>Risk, as an effect of uncertainty, is associated with every human activity. Like any other industry, construction companies are eager to reduce the uncertainty of reluctant events. A well-planned risk communication system could contribute to the success of a construction project. A proper announcement protocol could be a mitigating lever for identified or unidentified risks during planning and monitoring processes. This research aims to present a risk communication management system (RCMS) for construction companies involved in large projects. The proposed model includes a step-by-step communication procedure considering the authority level within the organisational hierarchical structure. The model aims to remove the ambiguity of risk communications during the construction process under uncertain conditions. It leaves no or little room for the emergence of unplanned risks. The proposed communication structure has been implemented in GRC cladding construction projects, and the risk communication time and response have been significantly improved.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/emj-2023-00312023-12-29T00:00:00.000+00:00Smart Fruit Growing Through Digital Twin Paradigm: Systematic Review and Technology Gap Analysishttps://sciendo.com/article/10.2478/emj-2023-0033<abstract> <title style='display:none'>Abstract</title> <p>This article provides a systematic review of innovations in smart fruit-growing. The research aims to highlight the technological gap and define the optimal studies in the near future moving toward smart fruit-growing based on a systematic review of literature for the period 2021–2022. The research object is the technological gap until the smart fruit-growing. The research question of the systematic review was related to understanding the current application of vehicles, IoT, satellites, artificial intelligence, and digital twins, as well as active studies in these directions. The authors used the PRISMA 2020 approach to select and synthesise the relevant literature. The Scopus database was applied as an information source for the systematic review, completed from 10 May to 14 August 2022. Forty-three scientific articles were included in the study. As a result, the technology gap analysis was completed to highlight the current studies and the research trends in the near future moving toward smart fruit-growing. The proposed material will be useful background information for leaders and researchers working in smart agriculture and horticulture to make their strategic decisions considering future challenges and to optimise orchard management or study directions. Considering the current challenges, authors advise paying attention to decision-making, expert, and recommendation systems through the digital twin paradigm. This study will help the scientific community plan future studies optimising research to accelerate the transfer to new smart fruit-growing technologies as it is not sufficient to develop an innovation, but it must be done at the appropriate time.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/emj-2023-00332023-12-29T00:00:00.000+00:00Generative AI in the Manufacturing Process: Theoretical Considerationshttps://sciendo.com/article/10.2478/emj-2023-0029<abstract> <title style='display:none'>Abstract</title> <p>The paper aims to identify how digital transformation and Generative Artificial Intelligence (GAI), in particular, affect the manufacturing processes. Several dimensions of the Industry 4.0 field have been considered, such as the design of new products, workforce and skill optimisation, enhancing quality control, predictive maintenance, demand forecasting, and marketing strategy. The paper adopts qualitative research based on a critical review approach. It provides evidence of the GAI technology support in the mentioned areas. Appropriate use of emerging technology allows managers to transform manufacturing by optimising processes, improving product design, enhancing quality control, and contributing to overall efficiency and innovation in the industry. Simultaneously, GAI technologies facilitate predictive analytics to forecast and anticipate future demand, quality issues, and potential risks, improve a marketing strategy and identify market trends.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/emj-2023-00292023-12-29T00:00:00.000+00:00Comparative Study on Workforce Transformation Strategy and SME Policies in Indonesia and Malaysiahttps://sciendo.com/article/10.2478/emj-2023-0024<abstract> <title style='display:none'>Abstract</title> <p>This study aims to compare efforts to digitise SMEs in Indonesia and Malaysia, particularly in the Central Java and Kuala Terengganu regions, especially in the cultural context and perceptions of SME owners, in terms of workforce transformation. Data were collected on the creative industry SMEs in Central Java and Kuala Terengganu, with a sample size of 241 at each location. The collected data were then analysed using the ANOVA difference test and the SPSS regression test. This study’s results prove differences in the levels of agile leadership, organisational ambidexterity and workforce transformation in SMEs in Central Java, Indonesia and Kuala Terengganu, Malaysia. Agile leadership and organisational ambidexterity have also been shown to positively and significantly affect workforce transformation. The results of this study contribute to improving the theoretical understanding of SME workforce transformation in Indonesia and Malaysia, particularly the development of academic science in management. In addition, this study also provides information, recommendations, and references to SME entrepreneurs related to strategic planning to optimise performance in maintaining the sustainability of their businesses. This study also provides a practical contribution as a reference for improving the performance of SMEs in Indonesia and Malaysia.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/emj-2023-00242023-12-29T00:00:00.000+00:00Towards Intelligent Automation (IA): Literature Review on the Evolution of Robotic Process Automation (RPA), its Challenges, and Future Trendshttps://sciendo.com/article/10.2478/emj-2023-0030<abstract> <title style='display:none'>Abstract</title> <p>Robotic Process Automation (RPA) and Artificial Intelligence (AI) integration offer great potential for the future of corporate automation and increased productivity. RPA rapidly evolves into Intelligent Process Automation (IPA) by incorporating advanced technologies and capabilities beyond simple task automation. The paper aims to identify the organisational, technological, and human-centred challenges that companies face in transitioning from RPA to IPA. The research process involved conducting the scientific literature search using the ResearchRabbit AI tool, which provided a set of reference papers relevant to the formulated research questions. As a result of the conducted literature review, the authors identified key challenges and possible countermeasures for companies transitioning from RPA to IPA. The resulting collection of reference scientific articles formed the basis for this study’s content and substantive analysis. Furthermore, this study contributes by identifying artificial intelligence techniques and algorithms, such as Natural Language Processing (NLP), Machine Learning (ML), Deep Learning (DL), predictive analytics, and others, that can be integrated with RPA to facilitate the transition to IPA. The paper also offers insights into potential future research areas.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/emj-2023-00302023-12-29T00:00:00.000+00:00Manufacturing equipment retrofitting towards Industry 4.0 standards — a systematic overview of the literaturehttps://sciendo.com/article/10.2478/emj-2023-0017<abstract> <title style='display:none'>Abstract</title> <p>The main purpose of this paper is a systematic literature review on retrofitting tools, equipment, and infrastructure in the industrial domain. The methods used for the research were a systematic literature review: publication analysis, selection of databases, and appropriate modification of queries in individual databases. Findings were presented using a map of keywords, clusters, and charts. The main result of the conducted research was the identification of the main trends in the retrofitting area. The trends developed within the review can support further research into the direction of retrofitting methods and the factors determining the choice of specific techniques and tools in the digitalisation of manufacturing enterprises.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/emj-2023-00172023-10-10T00:00:00.000+00:00Methodology of an interpretive structural map construction for social commerce successhttps://sciendo.com/article/10.2478/emj-2023-0023<abstract> <title style='display:none'>Abstract</title> <p>The factors influencing consumer purchase decisions in electronic commerce platforms and the interrelationships of each element are prevalent in the domain literature. However, a comprehensive analysis of the complex interrelationships among the success factors remains unexplored, especially in a social commerce context. To address the gap, this work evaluates the relationship structure and determines the critical factors using interpretive structural modelling (ISM). On the other hand, the Matrice d’Impacts Croisés Multiplication Appliquée á un Classement (MICMAC) is introduced to analyse the interaction of the factors and recognise the most relevant among them. In demonstrating the ISM-MICMAC analysis, this work performed a case study evaluating 13 factors of social commerce success for food products derived from a previous study. The findings of this work suggest that timeliness, data privacy policy, and Internet connectivity drive most other factors. Thus, focusing the resources on augmenting these factors consequently improves other factors. These findings suggest that sellers must streamline their overall service chain to maintain timeliness in their transactions, safeguard consumers’ data privacy, and uphold consumer communication efficiency to maximise Internet connectivity. These insights provide useful information to help decision-makers in the food industry allocate resources and encourage more consumers for social commerce. Several managerial insights were discussed.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/emj-2023-00232023-10-10T00:00:00.000+00:00Multi-skilled workforce scheduling with training and welfare considerationshttps://sciendo.com/article/10.2478/emj-2023-0018<abstract> <title style='display:none'>Abstract</title> <p>Flexibility in workforce scheduling in services is necessary to reduce the impact of demand uncertainty, absenteeism, and desertion while maintaining high service levels. This paper studies the workforce scheduling problem, including multiple skill accumulation, training, and welfare, as well as flexibility for employees and the company. All these elements are modelled and included in a mixed-integer linear programming (MILP) model that maximises their accumulated skill level. A real case study based on the scheduling of lab assistants to laboratory practices at a university in Colombia is used to generate numerical experiments. Different experiments were conducted, and the results show that the level of skill achieved is highly sensitive to the number of assistants and the number of allocations. The experiments also showed that, while keeping the same number of lab assistants, it is possible to include flexibility and welfare constraints. Finally, the proposed model can generate schedules that achieve high levels of skills and meet the different constraints of the model, including balance, accumulation, demand and welfare.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/emj-2023-00182023-10-10T00:00:00.000+00:00The importance of resources in achieving the goals of energy companieshttps://sciendo.com/article/10.2478/emj-2023-0020<abstract> <title style='display:none'>Abstract</title> <p>The fundamental transformation of the global energy sector challenges Polish energy companies to define new organisational goals. To a large extent, these objectives determine an energy company’s competitive position and ability to develop in the long term. However, achieving the set goals requires adequate resources. This paper mainly aims to identify and assess the resources used to achieve organisational goals in Polish energy companies. Based on a literature review and data collected from 110 Polish energy companies, the authors identified and assessed resources for achieving their organisational goals. The study confirmed that the organisational goals pursued by energy companies are interrelated. Analysis of the results of the basic organisational goals postulated by Polish energy companies showed that economic goals, such as “market share growth”, “implementation of innovative solutions”, and “quality of products/services”, are among the most important. The study showed that the resources held by energy companies are important for implementing separate organisational goals. Human resources received the highest rating and were considered of the greatest importance for the implementation of the goals of “sector development”, “uninterrupted energy supply”, and “sustainable development”. The paper assesses and discusses the characteristics of Polish energy companies’ organisational resources and organisational goals. The contribution of this study is the highlighted importance of resources in achieving the organisational goals of Polish energy companies. The main practical implication of this article is to stress the existence of links between the individual goals of companies in the energy sector and to highlight the importance of the different resource categories they possess for achieving specific objective bundles.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/emj-2023-00202023-10-10T00:00:00.000+00:00Industry 4.0 technologies and managers’ decision-making across value chain. Evidence from the manufacturing industryhttps://sciendo.com/article/10.2478/emj-2023-0021<abstract> <title style='display:none'>Abstract</title> <p>The paper aims to identify how Industry 4.0 technologies affect the quality and speed of the managers’ decision-making process across the different stages of the value chain, based on the example of the manufacturing sector. The paper adopts qualitative research, based on nine in-depth interviews with key informants, to capture senior executives’ experiences with implementing Industry 4.0 technologies in their organisations. The research is focused on three manufacturing industries: the automotive, food and furniture industries. The research shows that depending on the stage of the value chain, different Industry 4.0 technologies are more suitable for the support of managers’ decisions. Various Industry 4.0 technologies support decision-making at different stages of the manufacturing value chain. In the Design stage, 3D printing and scanning technologies play a crucial role. In the case of Inbound Logistics, robotisation, automation, Big Data analysis, and Business Intelligence are most useful. During the Manufacturing stage, robotisation, automation, 3D printing, scanning, Business Intelligence, cloud computing, and machine-to-machine (M2M) integration enable quick decision-making and speed up production. Sensors and the Internet of Things (IoT) optimise distribution in the Outbound Logistics stage. And finally, Business Intelligence supports decisions within the Sales and Marketing stage. It is also the most versatile technology among all particular stages. The paper provides empirical evidence on the Industry 4.0 technology support in decision-making at different stages of the manufacturing value chain, which leads to more effective value chain management, ensuring faster and more accurate decisions at each value-chain stage. When using properly selected Industry 4.0 technologies, managers can optimise their production processes, reduce costs, avoid errors and improve customer satisfaction. Simultaneously, Industry 4.0 technologies facilitate predictive analytics to forecast and anticipate future demand, quality issues, and potential risks. This knowledge allows organisations to make better decisions and take proactive actions to prevent problems.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/emj-2023-00212023-10-10T00:00:00.000+00:00Reporting sustainable development in Polish commercial bankshttps://sciendo.com/article/10.2478/emj-2023-0019<abstract> <title style='display:none'>Abstract</title> <p>The article aims to present sustainable development reporting based on data obtained from Polish commercial banks, considering different approaches and scopes of presenting non-financial data, even though specific guidelines have been issued. The research procedure included a literature review of Polish and foreign literature and research using the case study method. The article presents examples of environmental, social and governance (ESG) activities reported by selected commercial banks in Poland in a case study. ESG activities are reported separately and presented as part of annual reports. Many of the banks’ activities presented in the survey can serve as a model for others, as not all banks have a clearly written ESG strategy. A positive effect of reporting ESG activities is the clarification of indicators, such as reducing greenhouse gas emissions, eliminating exposure to the extractive sector or increasing “green” financing. This article can contribute to showing role models for banks in three areas, i.e., environmental, social and corporate governance. As a result, the authors tried to propose solutions where sector organisations could compare themselves in non-financial areas.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/emj-2023-00192023-10-10T00:00:00.000+00:00Neural network modelling of non-prosperity of Slovak companieshttps://sciendo.com/article/10.2478/emj-2023-0016<abstract> <title style='display:none'>Abstract</title> <p>Early identification of potential financial problems is among important companies’ risk management tasks. This paper aims to propose individual and ensemble models based on various types of neural networks. The created models are evaluated based on several quantitative metrics, and the best-proposed models predict the impending financial problems of Slovak companies a year in advance. The precise analysis and cleaning of real data from the financial statements of real Slovak companies result in a data set consisting of the values of nine potential predictors of almost 19 thousand companies. Individual and ensemble models based on MLP and RBF-type neural networks and the Kohonen map are created on the training sample. On the other hand, several metrics quantify the predictive ability of the created models on the test sample. Ensemble models achieved better predictive ability compared to individual models. MLP networks achieved the highest overall accuracy of almost 89 %. However, the non-prosperity of Slovak companies was best identified by RBF networks created by the boosting and bagging technique. The sensitivity of these models is about 87 %. The study found that models based on neural networks can be successfully designed and used to predict financial distress in the Slovak economy.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/emj-2023-00162023-10-10T00:00:00.000+00:00Managerial approaches, frameworks, and practices for business model application in public services management in the VUCA environmenthttps://sciendo.com/article/10.2478/emj-2023-0022<abstract> <title style='display:none'>Abstract</title> <p>Significant gaps in public services management were highlighted when service-dominant logic emerged in services science, resulting in fundamental changes in attitudes. The business model application in public services was initiated by offering public service logic. However, this concept requires justification of its interfaces with management approaches, frameworks, and practices. The VUCA (Volatility, Uncertainty, Complexity, and Ambiguity) environment has changed the existing managerial approach in organisational performance and services management. This paper aims to highlight the key aspects and justify the application of services management approaches, frameworks, and practices (Agile practices, customer experience management frameworks, and the design thinking approach) that coincide with the business model approach in public services management (public service logic) in a VUCA environment. In this paper, the Cochrane Guide to Literature Reviews was loosely followed. The focus was on academic publications and such expert sources as webinars for practitioners. Only publications and expert sources in English were included. The Scopus search engine was used for academic sources. Publications covering at least two of the following domains were included: Customer experience, business model, Agile practices, design thinking approach, public services, and VUCA. The expert sources were selected using purposive sampling when communities of practice were identified by authors with expert knowledge, and the main communication channels within each community of practice were sampled. The analysis showed that public services are defined as public goods that the State’s government commits to deliver in line with public values by applying a customer-centric approach. Integrating the design thinking approach and Agile practices help create customer-centric solutions for the customer experience management framework as design thinking helps understand what to do, while Scrum (one of Agile practices) gives the autonomy in deciding how to do it. Each analysed managerial method contributes uniquely to improving public services management in a VUCA environment.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/emj-2023-00222023-10-10T00:00:00.000+00:00Measuring quality perception of public services: customer-oriented approachhttps://sciendo.com/article/10.2478/emj-2023-0015<abstract> <title style='display:none'>Abstract</title> <p>The focus of this research is on assessing the perception of public service quality through a customer-centred approach. Public service quality comprises multiple factors that are prioritised differently by customers. Therefore, the study aims to conduct a literature review to identify the primary quality dimensions of public services and evaluate the heterogeneity of their perception within the context of Lithuania. The research measures the user perceptions of public service quality. The literature review allowed for identifying service quality indicators and grouping them into dimensions based on unifying characteristics. Such identification of service quality dimensions grounded the research methodology. An adapted SERVQUAL model was used to analyse data collected by a survey to interview customers of Lithuanian public service organisations. Logit and probit models were applied to examine the effect of socio-demographic characteristics and the type of service on customer perceptions of different quality aspects of the provided public services. Explored heterogeneity of attitudes and detailed analysis of socio-demographic factors revealed that women with higher education are the most satisfied users of public services, while less educated men usually have a negative attitude towards the quality of public services. The study confirmed that marital status and income level are not related to customer satisfaction with service quality. Although gender, age, family size, education level, and employment status explain heterogeneity in customer satisfaction, they still account for only a small amount of variance compared to the place of residence and type of service. The study is a significant contribution to the field of service engineering as it introduces a systematic approach to the development of service quality, incorporating models and methods that enable the assessment of service quality and efficiency. The literature review has identified several research gaps related to public service quality, including a lack of research on general public services and areas such as tourism, real estate management, fire protection and rescue.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/emj-2023-00152023-06-30T00:00:00.000+00:00Improving the assessment of the diversification of construction companieshttps://sciendo.com/article/10.2478/emj-2023-0011<abstract> <title style='display:none'>Abstract</title> <p>Various indicators are used to determine the level of company diversification. Their adequacy largely depends on the structure of the production programme. Its essential feature is the comparative weight of the main product in the total scope of the company’s work. In this situation, the intensity of the diversification process is reflected by the decrease in the volume of this product due to the inclusion of new products in the production programme. In this case, the adequacy of the diversification indicator can be reflected by comparing the scale of the main product with changes in the value of these indicators. The adequacy will be higher with more changes in the values of diversification indicators corresponding to changes in the volumes of the main product. Four indicators of corporate diversification are the most well-known and widely used: the Berry index, the entropy measure, Utton’s measure and the DG index. All of them have both strong and weak sides, so it is important to determine situations of the company’s production programme in which diversification indicators are appropriate to use, i.e., in which situations their adequacy is the greatest. The research has established that if the comparative weight of the main product of the production programme in the total scope of work is greater than 0.5, then the adequacy of the entropy measure and index DG is higher compared to the Berry index and Utton’s measure. If it is lower than 0.5, the other two diversification indicators should be used. The obtained results will help to more efficiently manage the process of diversification as a company’s development strategy.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/emj-2023-00112023-06-30T00:00:00.000+00:00en-us-1