Search Results (44)

In a business environment with rapidly growing digital technologies, knowledge management (KM) capability is an indispensable source for enterprise innovation activities. Nevertheless, there is limited understanding of the specific KM capability that leads to sustainable business model innovation (SBMI). This study therefore aimed to investigate the internal relationship between KM capability and SBMI by leveraging dynamic capability theory. A hierarchical regression analysis (HRA) and a fuzzy set qualitative comparative analysis (fsQCA) are used to analyze a sample of 115 Chinese innovative enterprises. The results indicate that organizational structure promotes information technology by improving human capital, and that information technology then stimulates collaboration depth by expanding collaboration breadth, thereby driving SBMI. Specifically, human capital, information technology, collaboration breadth, and collaboration depth play significant chain-mediating roles in the relationship between organizational structure and SBMI. This study contributes to the literature on KM and innovation management, extends the use of low-order and high-order dynamic capabilities in DCT, and assists managers in developing SBMI effectively. Full article

The selection of an appropriate cloud platform represents a highly important strategic decision for any IT company. In pursuit of business optimization, cost reduction, improved reliability, and enhanced market competitiveness, selecting the most suitable cloud platform has become a major practical challenge. This paper proposes a novel two-stage multi-attribute decision-making (MADM) model, enhanced through the use of interval type-2 fuzzy sets (IT2FMADM). This was demonstrated through a case study in an IT company based in Serbia. In the first stage, three experts from the company were surveyed to assess the relative importance of the attributes, and their evaluations were aggregated using the fuzzy harmonic mean operator. As a result, unified fuzzy weight vectors were obtained. In the second stage, two MADM methods extended with interval type-2 fuzzy sets, namely COmplex PRoportional Assessment (IT2FCOPRAS) and Evaluation based on Distance from Average Solution (IT2FEDAS), were applied to support the selection of the most suitable cloud platform. Each platform was evaluated by decision-makers (DMs), who reached a consensus in their assessments, supported by data from company records. A comparative analysis of the results revealed that different methods may produce varying rankings of alternatives, particularly when the alternatives are objectively similar in their characteristics. Nevertheless, the proposed model can serve as a highly useful decision-support tool for company management. Full article

The rapid expansion of online grocery shopping has intensified the need for strategically located distribution hubs that ensure efficient and sustainable operations. Traditional location models emphasize economic and logistical factors but often neglect energy efficiency and environmental sustainability. This paper proposes a hybrid decision-making model that integrates the analytic hierarchy process (AHP) and the spherical fuzzy technique for order of preference by similarity to ideal solution (SFTOPSIS) to address the complexities of delivery hub location selection. The AHP is used to determine the relative importance of key decision-making criteria, including cost, accessibility, infrastructure, competition, and sustainability, while SFTOPSIS ranks the candidate locations based on their proximity to the ideal solution. Spherical fuzzy sets allow for a more nuanced treatment of uncertainty, improving decision-making accuracy in dynamic environments. The results demonstrate that this hybrid approach effectively manages incomplete and uncertain data, delivering a robust ranking of candidate locations. By incorporating sustainability as a key factor, this study provides a structured and adaptive framework for businesses to optimize logistics operations in the post-pandemic landscape. The proposed methodology not only enhances decision-making in location selection but contributes to the development of more resilient and sustainable supply chain strategies. Full article

The need to review maritime education has been highlighted in the relevant literature. Maritime curricula should incorporate recent technological advances, as well as address the needs of the maritime sector. In this paper, the Fuzzy Delphi Method (FDM) and the Fuzzy Analytic Hierarchy Process (FAHP) are utilized in order to propose a fuzzy multicriteria decision-making (MCDM) methodology that can be used to assess the importance of new technologies in maritime education and design a fuzzy evaluation model that can assist in maritime education policy-making. This study integrates the perspectives of the main maritime education stakeholders, namely, lecturers and maritime sector management. We selected data from a group of 19 experienced maritime professors and maritime business managers. The results indicate that new technologies such as artificial intelligence (AI), augmented and virtual reality (AR/VR), the Internet of Things (IoT), digital twins (DTs), and cybersecurity, as well as eLearning platforms, constitute a set of requirements that maritime education policies should meet by designing their curricula appropriately. This study suggests that fuzzy logic MCDM methods can be used as a human-centered AI approach for developing explainable education policy-making models that integrate stakeholder requirements and capture the subjectivity that is often inherited in their perspectives. Full article

Today’s sharp competition has forced organizations to adopt effective improvement paradigms, including lean, agile, green, and resilience (LARG). However, an assessment tool is necessary to monitor the progress of LARG adoption and evaluate its effectiveness. This research, therefore, developed an index for assessing the effectiveness of LARG paradigms by evaluating their principles and practices with experts’ fuzzy evaluations. Initially, thorough research on LARG paradigms was conducted to determine the paradigm principles and their measures and prepare a comprehensive LARG survey. The Delphi method with four experts was used to rate item measures of LARG based on a five-point Likert scale. The principles and measures of each paradigm were represented by triangular fuzzy membership functions. Then, defuzzified values were obtained for each principle and set as inputs in the fuzzy inference system (FIS) to obtain a crisp value for each paradigm. Next, the defuzzified values of lean, agile, and green (LAG) were input in the FIS to obtain a crisp LAG index. Finally, the defuzzified values of the LAG and resilience (R) were measured and then inserted as inputs in the FIS to obtain a comprehensive defuzzified LARG value. The effectiveness of the proposed LARG framework was validated in pharmaceutical and chemical organizations. The results revealed that the LARG index is an effective tool for evaluating lean, agile, green, and resilience paradigms for both organizations. In conclusion, the LARG index provides valuable support to decision-makers in determining a business’s weaknesses and strengths and guides technical managers to possible improvement actions to enhance competitiveness and sustainability. Full article

(1) Background: Loyalty programmes are business strategies aimed at increasing customer fidelity to brands. One of the most promising technologies of the 21st century is blockchain, whose application to the management of loyalty programmes can increase transparency and reliability, enable interoperability, and facilitate centralised management. (2) Methods: This study evaluates the antecedents of the acceptance of blockchain-based loyalty programmes (BBLPs) using a model grounded in the technology acceptance model UTAUT2. The four basic constructs of UTAUT, which we call the UTAUT-baseline, are considered explanatory factors: performance expectancy (PER), effort expectancy (EFF), social influence (SOC), and facilitating conditions (FAC). Additionally, we consider the constructs introduced in UTAUT2: hedonic motivation (HED) and perceived price value (PRI), to which we add innovativeness (INN) and trust (TRU), and we refer to these as UTAUT-extended, along with the moderating variables of UTAUT and UTAUT2: gender, age, and experience. The analytical approach used is complexity theory, which aims to capture the configurations that lead to both acceptance and rejection positions regarding BBLPs. This analysis is performed via fuzzy set qualitative comparative analysis (fsQCA). (3) Results: Eight explanatory configurations of the acceptance of BBLPs have been obtained, in which the presence of all UTAUT-baseline and UTAUT-extended constructs is a condition in at least three prime implicates. The constructs with the greatest presence as core conditions are PER, EFF, and TRU. On the other hand, nine configurations leading to the rejection of BBLPs have been identified. The absence of all UTAUT-baseline and UTAUT-extended variables is a condition in at least three configurations. The core conditions with the greatest presence in the rejection of BBLPs are the lack of FAC, HED, and PRI. (4) Practical implications: The results obtained are of great interest to business owners, as they allow for the characterisation of different profiles of people potentially engaged with BBLPs, as well as the profiles of consumers reluctant to adopt them. Full article

The digital transformation (DT) encompasses profound technological changes. Businesses face the challenge of adapting their activities to the pace of new technologies to increase the efficiency of business processes, improve the customer experience, and create innovative value propositions while recognizing the importance of sustainability. This research focuses on how family businesses, which are a relevant part of global economic activity and job creation, address the challenges associated with the DT. Based on the case of the automotive retail sector in a small European country characterized by the high acceptance of technologies, we use fuzzy-set qualitative comparative analysis (fsQCA) to understand how critical success factors (causal conditions) combine towards adopting technologies representing different perspectives of the DT. The results confirm the existence of multiple configurations based on the importance of organizational culture, change management, knowledge, human capital, IT systems, and DT strategy towards the adoption of customer relationship management, digital marketing, and social networks technologies, thus helping family businesses to understand the adoption of these technologies leading to organizational success in the context of the DT. Full article

Using digital technologies is essential to gain a competitive advantage in the global market by adapting to new business models. While digital technologies make business processes efficient, they enable companies to make faster and more accurate decisions by automating daily and routine process tasks. Robotic process automation (RPA) automates routine and repetitive business processes, allowing many jobs performed by humans to be performed faster. This way, advantages such as reduced error rates, reduced costs, increased production speed, and labor productivity are provided. For the successful implementation of RPA, potential risks need to be considered. In this study, failure mode and effect analysis (FMEA) based on decomposed fuzzy sets (DFSs), a new extension of intuitionistic fuzzy sets, has been used to evaluate subjectiveness in expert judgments. Differing from the other extensions of fuzzy set theory, the advantage of DFSs is to simultaneously consider decision-makers’ optimistic and pessimistic answers. Thus, the answer given by the decision-maker to the positive and negative questions on the same subject defines the indeterminacy of the decision-maker, and the method takes this indeterminacy into account in the evaluation. This study assesses and evaluates the potential risks of six digital robots in process automation. Thirteen risks were individually assessed for each automated process. This study found “Sustainability challenge” critical in three processes, “Absence of governance management” in two, and “Security“ in one. Variability in risk importance arose from process vulnerabilities. Full article

There is a clear European Strategy to transition by 2050 from a fossil fuel-based economy to a completely new system based on renewable energy resources, with electricity as the main energy carrier. Positive Energy Districts (PEDs) are urban areas that produce at least as much energy as their yearly consumption. To meet this objective, they must incorporate distributed generation based on renewable systems within their boundaries. This article considers the fluctuations in electricity prices and local renewable availability and develops a PED model with a centralised energy storage system focused on electricity self-sufficiency and self-consumption. We present a fuzzy logic-based energy management system which optimises the state of charge of the energy storage solution considering local electricity production and loads along with the contracted electric tariff. The methodology is tested in a PED comprising 360 households in Bilbao (a city in the north of Spain), setting various scenarios, including changes in the size of the electric storage, long-term climate change effects, and extreme changes in the price of energy carriers. The study revealed that the assessed PED could reach up to 75.6% self-sufficiency and 76.8% self-consumption, with climate change expected to improve these values. On economic aspects, the return on investment of the proposal ranges from 6 up to 12 years depending on the configuration choice. Also, the case that boosts the economic viability is tight to non-business as usual (BaU), whichever event spiked up the prices or climate change conditions shortens the economic variables. The average bill is around 12.89 EUR/month per house for scenario BaU; meanwhile, a catastrophic event increases the bill by as much as 76.7%. On the other hand, climate crisis events impact energy generation, strengthening this and, as a consequence, slightly reducing the bill by up to 11.47 EUR/month. Full article

Chinese family farms are continuously expanding; they are also facing various business risks that lead to a shorter lifespan. This paper constructed a family farm business risk assessment model that combined a hesitant fuzzy linguistic term sets (HFLTS) model with a hesitant fuzzy weighted average (HFWA) operator. On the basis of the factor analysis, this study built a family farm indicator system that included the natural, technical, market, policy, society, and management risk. The HFLTS was used for the assessment of weights in pairwise comparison matrices, and the HFWA operator was used as an aggregation operator to calculate the business risk score of family farms. For our case study, a method comparison analysis was also performed to check the validity of the results obtained by our risk assessment model. Full article

Innovation is crucial for achieving and maintaining a competitive edge, especially evident in the digital business landscape, where the fourth and fifth industrial revolutions are occurring concurrently. Leadership behavior significantly influences the direction of organizations toward innovation. This study investigated whether a propensity for risk taking, along with a commitment to diversity and agility, promotes or impedes leaders’ innovative behavior. Fuzzy-set qualitative comparative analysis was employed to assess the data gathered from an online survey of 119 global leaders. The results exposed four distinct routes to fostering innovative behavior and three paths leading to noninnovative behavior that should be evaded. All conditions play a vital role in triggering innovative behavior. Conversely, the lack of these conditions can result in noninnovative leadership. This study’s novelty rests on the empirical evidence it provides about the paths guiding leaders toward innovative behavior and avoiding the danger of noninnovative leadership. These findings can assist managers and HR departments in pursuing certain paths for hiring and training managers to boost innovative behavior and preclude paths leading to noninnovative conduct. Full article

Over the past few years, the uncertain business environment has shaped the resilient development thinking of firms. Measuring and predicting innovation resilience plays a crucial role in fostering the sustainable development of enterprises. This paper used the entropy-weight TOPSIS model and FGM(1,1) model to measure the innovation resilience of companies based on an indicator system, covering aspects such as tolerance for factor scarcity, R&D safety, core technology self-sufficiency, and organizational change capacity. The results show that the MAPE of the FGM(1,1) model is 0.0136, which is lower than that of the GM(1,1) model, with the predicted annual growth rate of the resilience being −0.95% from 2020 to 2025. Consequently, the study investigated what policy configuration may improve innovation resilience using the fuzzy-set qualitative comparative analysis (fsQCA) model. It identified four policy configuration paths, of which the combination of a tax policy for an additional deduction of enterprise R&D expenses and an income tax reduction policy is an effective policy configuration. This research expands the application of the FGM(1,1) model and inspires managers to develop innovative policies to enhance corporate resilience. Full article

This study aims to develop a framework by incorporating well-proven project management techniques to help startup owners effectively set up ventures and secure early-stage financing. Startups not only open ways for innovative and updated technologies in the markets but also bring employment opportunities in a country that eventually increase productivity and the per capita income of a country. Despite all the benefits, the success rate of startups is meager, especially in developing countries, due to ineffective management and vague business plans. Therefore, this study aims to facilitate entrepreneurs using well-proven project management techniques from the literature and devise a new framework applied to a business case, as discussed in this paper. This study presents an approach to project management techniques for smartphone app-based startups. This study utilizes the fuzzy PERT (FPERT) for the best completion time and budget estimates. Experts’ opinions from eight private limited companies have been analyzed using FPERT. The critical path method (CPM) is also used to schedule activities. Finally, a techno-economic analysis is also performed to show the growth potential of such a startup, e-Karsaz. This study aims to help startups secure early-stage financing. Tech-based business ideas need to be commercialized in developing countries like Pakistan. There is a need to show long-term profitability to make an idea stand out among others and secure early-stage financing. The scope of project management techniques is confined to construction-based projects. The results show that it would take around 692 days for the e-Karsaz startup to become fully operational, with the capital budget estimated at around PKR 1.3 billion. The techno-economic analysis shows the project is economically viable with an internal rate of return (IRR) equal to 92 percent and a benefit-to-cost ratio (BCR) equal to 10. The sensitivity analysis, including five scenarios of weighted average cost of capital (WACC), shows that the project remains economically viable even if the required rate of return goes over 20 percent. This study is helpful for startups to make time and budget estimates and to show the growth potential to secure early-stage financing. Full article

The current global economic status quo is widely seen as unsustainable in the food sector. The field of sustainability science is still rather fragmented, covering a wide range of techniques and issues, despite the large number of publications in this area. Due to population growth, the food supply chain (FSC) and farmers have to produce more food. The UN estimates that one-third of edible food is wasted, producing greenhouse gases. A balance must be struck between company operations and social, environmental, and economic activities for sustainable development of the FSC. To assist FSC organizations in managing sustainable advancement, this study created a methodology for the assessment of sustainable performance. We provide a sustainable assessment system using a fuzzy analytic hierarchy process, fuzzy VIKOR, and fuzzy TOPSIS. Our research framework evaluated the sustainability of three cooperative-society-run Indian dairy firms. Our study gives environmental criteria the highest weight (0.33) and social criteria the lowest (0.16), with economic reasons (0.306) and business operations (0.204) falling in the middle. Supply chain costs, on average, are given the highest weight, and capacity utilization, the lowest weight. Three dairy industries are ranked (DPI3, DPI1, and DPI2) based on sustainable performance. By modifying the maximum set utility value and validating VIKOR results with TOPSIS, we have checked the robustness of this performance assessment tool. This research aids dairy businesses in achieving several Sustainable Development Goals, including sustainable production and consumption, through the regular assessment of their sustainable performance. Full article

The success of an organization hinges upon the effective utilization of its human resources, which serves as a crucial developmental factor and competitive advantage, and sets the organization apart from others. Evaluating staff productivity involves considering various dimensions, notably structural, behavioral, and circumferential factors. These factors collectively form a three-pronged model that comprehensively encompasses the facets of an organization. However, assessing the productivity of employees poses challenges, due to the inherent complexity of the humanities domain. Fuzzy logic offers a sound approach to address this issue, employing its rationale and leveraging a fuzzy inference system (FIS) as a sophisticated toolbox for measuring productivity. Fuzzy inference systems enhance the flexibility, speed, and adaptability in soft computation. Likewise, their applications, integration, hybridization, and adaptation are also introduced. They also provide an alternative solution to deal with imprecise data. In this study, we endeavored to identify and measure the productivity of human resources within a case study, by developing an alternative framework known as an FIS. Our findings provided evidence to support the validity of the alternative approach. Thus, the utilized approach for assessing employee productivity may provide managers and businesses with a more realistic asset. Full article