Search results

This study aims to identify significant factors, analyse them using the consistent fuzzy preference relations (CFPR) method and forecast the probability of successful deployment of the internet of things (IoT) and cloud computing (CC) in Gujarat, India’s building sector.

From the previous studies, 25 significant factors were identified, and a questionnaire survey with personal interviews obtained 120 responses from building experts in Gujarat, India. The questionnaire survey data’s validity, reliability and descriptive statistics were also assessed. Building experts’ opinions are inputted into the CFPR method, and priority weights and ratings for probable outcomes are obtained to forecast success and failure.

The findings demonstrate that the most important factors are affordable system and ease of use and battery life and size of sensors, whereas less important ones include poor collaboration between IoT and cloud developer community and building sector and suitable location. The forecasting values demonstrate that the factor suitable location has a high probability of success; however, factors such as loss of jobs and data governance have a high probability of failure. Based on the forecasted values, the probability of success (0.6420) is almost twice that of failure (0.3580). It shows that deploying IoT and CC in the building sector of Gujarat, India, is very much feasible.

Previous studies analysed IoT and CC factors using different multi-criteria decision-making (MCDM) methods to merely prioritise ranking in the building sector, but forecasting success/failure makes this study unique. This research is generally applicable, and its findings may be utilised for decision-making and deployment of IoT and CC in the building sector anywhere globally.

In this study, the researchers explored the predictive powers of corporate cultural factors and self-efficacy on Pakistan's public sector bank employees' organizational commitment.

The researchers designed a co-relational study based on cross-sectional data using a questionnaire to collect the data from the Pakistan public sector banks' managers, assistant managers and operational managers. Consequently, the researchers based this study's findings on the 270 valid responses to the questionnaire.

This study's findings reveal that, except for teamwork, together with self-efficacy, the corporate cultural factors comprising organizational communication, training and development and reward and recognition have positive and significant impacts on organizational commitment. More specifically, self-efficacy plays a mediating role in terms of the relationships between organizational commitment and organizational communication, training and development and reward and recognition.

From establishing the most relevant corporate cultural factors, the researchers consider that this study's findings are helpful to policymakers and organizations in developing organizational commitment among employees. More practically in the case of Pakistan's public sector banks, the employees can improve employees' performance by recognizing the significance of the corporate cultural factors on employees' organizational commitment. In addition, the researchers consider that this study's findings can improve managerial efficiency which, in turn, can lead to the organizations becoming more successful.

In the context of Pakistan's public sector banks, this study's findings provide empirical insights to the relationships between the corporate cultural factors and organizational commitment. In addition, the findings provide insights to the role played by self-efficacy in mediating these relationships.

The demand for halal food products is increasing globally. However, fraudulent activities in halal products and certification are also rising. One strategy to ensure halal integrity in the food supply chain is applying halal blockchain technology. However, to date, a few studies have assessed the factors and variables that facilitate or hinder the adoption of this technology. Thus, this study aims to assess the significant factors and variables affecting the adoption of halal blockchain technology.

A Delphi-based approach, using semi-structured interviews, was conducted with three food companies (chicken slaughterhouses, milk processing plants and frozen food companies). The cognitive best–worst method determines the significant factors and variables to prioritise halal blockchain adoption decisions.

The results showed that the most significant factors were coercive pressure and halal strategy. Nineteen variables were identified to establish a valid hierarchical structure for halal blockchain adoption in the Indonesian food industry. The five significant variables assessed through the best–worst method were demand, regulator, supply side, sustainability of the company’s existence and main customers.

The proposed halal blockchain decision structure can assist food companies in deciding whether to adopt the technology.

This study proposes 19 variables that establish a valid hierarchical structure of halal blockchain adoption for the Indonesian food industry.

Significant developments in the service sector have been brought about by Industry 4.0. Automated digital technologies make it possible to upgrade existing services and develop modern industrial services. This study prioritizes critical factors for adopting Industry 4.0 in the Indian service industries.

The author identified four criteria and fifteen significant factors from the relevant literature that have been corroborated by industry experts. Models are then developed by the analytical hierarchy process (AHP) and analytical network process (ANP) approach to ascertain the significant factors for adopting Industry 4.0 in service industries. Further, sensitivity analysis has been conducted to determine the sensitivities of the rank of criteria and sub-factors to corroborate the results.

The outcome reveals the top significant criteria as organizational criteria (0.5019) and innovation criteria (0.3081). This study prioritizes six significant factors information technology (IT) specialization, digital decentralization of all departments, organizational size, smart services through customer data, top management support and Industry 4.0 infrastructure in the transition toward Industry 4.0 in the service industries.

The potential factors identified in this study will assist managers in determining strategies to effectively manage the Industry 4.0 transition by concentrating on top priorities when leveraging Industry 4.0. The significance of organizational and innovation criteria given more weight will lay the groundwork for future Industry 4.0 implementation guidelines in service industries.

Our research is novel since, to our knowledge, no previous study has investigated the potential critical factors from organizational, environmental, innovation and cost dimensions. Thus, the potential critical factors identified are the contributions of this study.

In today’s business world, adopting social commerce for day-to-day operations has increasingly become an important phenomenon. Several factors have been identified by previous researchers regarding the adoption of social commerce, but academic research is scarce on the relationship between the factors influencing social commerce adoption and small and medium-sized enterprises (SMEs) in the post-COVID-19 situation. This study aims to identify the impact of technological, environmental and entrepreneurial factors on the adoption of social commerce by SMEs in Sri Lanka.

A quantitative study utilised the deductive approach and collected data through a field survey by distributing a five-point Likert scale questionnaire to conveniently selected respondents from Sri Lankan SMEs. Structural equation modelling (SEM) was used for the analysis of 384 responses.

The results revealed that technological factors [technology availability (TA) and cost-effectiveness (CE)], environmental factors [bandwagon effect (BE)] and entrepreneurial factors [attitude (AT), innovativeness (IN) and IT knowledge (IK)] have a significant impact on the social commerce adoption of SMEs in Sri Lanka. This study, as the first of its type, offers insightful information on the influence of variables on the adoption of social commerce after the COVID-19 pandemic.

Similar to any research, this study also has inherent limitations. Due to time and financial restrictions, the study’s convenience sampling method was adopted. The study’s possible limitation is its narrow focus, which could mean that it only examines a select few social media (SM) networks. The study’s conclusions might be less generalised since it focused on the western province of Sri Lanka. Future studies should take a cross-cultural strategy to explore the influence of social commerce adoption to improve the generalisability of research findings.

This study provides an in-depth assessment of critical factors, facilitating policymakers, owners, leaders and managers (decision-makers) to gain insight into the real influencing factors on social commerce adoption and the significance of SM. The study helps them comprehend how outstanding governance and knowledge of influencing factors can boost SME success in various ways. For example, research reveals that various factors have a major influence on social commerce adoption.

There has been limited research conducted on social commerce adoption after the COVID-19 pandemic period; thus, this study looked at the variables influencing it amongst SMEs in a South Asian developing country like Sri Lanka after the pandemic lasted for two years. By placing a strong emphasis on the role of entrepreneurial characteristics and the available technology within one single framework in the context of SMEs and their involvement with social commerce adoption, this study contributes to the past literature by emphasising the role of several significant factors in SMEs' adoption of social commerce. Whilst previous studies looked at multiple factors influencing the adoption of social commerce globally, this study focussed on how these factors have a significant impact on SMEs in Sri Lanka.

This study developed a multi-perspective framework combining technological, environmental and entrepreneurial factors influencing SMEs to adopt social commerce. The study provides a contribution to the literature on social commerce adoption from the perspective of SMEs in a developing country like Sri Lanka after COVID-19. Exclusively, it examines the impact of entrepreneur-related factors on social commerce adoption.

Despite its devastating nature, the COVID-19 pandemic has also catalyzed a substantial surge in the adoption and integration of technological tools within economies, exerting a profound influence on the dissemination of information among participants in stock markets. Consequently, this present study delves into the ramifications of post-pandemic dynamics on stock market behavior. It also examines the relationship between investors' sentiments, underlying behavioral drivers and their collective impact on global stock markets.

Drawing upon data spanning from 2012 to 2023 and encompassing major world indices classified by Morgan Stanley Capital International’s (MSCI) market and regional taxonomy, this study employs a threshold regression model. This model effectively distinguishes the thresholds within these influential factors. To evaluate the statistical significance of variances across these thresholds, a Wald coefficient analysis was applied.

The empirical results highlighted the substantive role that investors' sentiments and behavioral determinants play in shaping the predictability of returns on a global scale. However, their influence on developed economies and the continents of America appears comparatively lower compared with the Asia–Pacific markets. Similarly, the regions characterized by a more pronounced influence of behavioral factors seem to reduce their reliance on these factors in the post-pandemic landscape and vice versa. Interestingly, the post COVID-19 technological advancements also appear to exert a lesser impact on developed nations.

This study pioneers the investigation of these contextual dissimilarities, thereby charting new avenues for subsequent research studies. These insights shed valuable light on the contextualized nexus between technology, societal dynamics, behavioral biases and their collective impact on stock markets. Furthermore, the study's revelations offer a unique vantage point for addressing market inefficiencies by pinpointing the pivotal factors driving such behavioral patterns.

The purpose of this study is to develop a decision-support framework that can be used by decision-makers to suspend public infrastructure projects. Additionally, the study also investigates how to select the most convenient infrastructure project for suspension.

The proposed framework includes an extensive set of factors and a novel comparison mechanism that can reveal the most convenient infrastructure project to be suspended. A comprehensible literature review and focus group discussion (FGD) sessions were conducted to identify factors that should be considered for suspension. Then, the neutrosophic analytic hierarchy process (N-AHP) method was used to determine the relative importance of the factors. Finally, the proposed comparison mechanism was demonstrated through a hypothetical case study and Technique for order of preference by similarity to ideal solution (TOPSIS) analysis.

Results showed that suspension decisions cannot be made merely based on “financial” factors. Instead, the other aspects, namely “Technical and managerial” and “Social and Environmental”, should also be taken into consideration. Second, factors related to the initial investment, cost of refinancing, cash flow, permits and approvals, insufficiency of bidders, degradation of the components, reputation, impact on stakeholders and criticality of the infrastructure were particularly elaborated as the most significant, needing the utmost attention of the decision-makers. Lastly, the results demonstrated that the proposed comparison mechanism has considerable potential to identify the most convenient infrastructure project for suspension.

Public infrastructure projects are often under pressure due to the inflationary state and economic stagnation of countries after major crises. The suspension decision for infrastructure projects necessitates comprehensible assessments to consider all consequences. Studies have widely investigated the contractual and legal aspects of project suspension in light of existing literature. However, little effort has been devoted to identifying the factors that decision-makers should consider before suspending a particular infrastructure project. Furthermore, existing literature does not investigate how to select the most convenient infrastructure project for suspension either. Thus, by developing a specific suspension framework for infrastructure projects by considering various factors, this study is the earliest attempt to examine the contract suspension mechanism of public infrastructure projects. In this respect, the study significantly contributes to the theory of contract management domain and has important managerial implications.

This study aims to identify the critical success factors of public private partnership (PPP) power projects in Ghana and further evaluates the most significant critical success factors (CSFs) influencing both the public and private sector participation in PPP power projects.

Ranking-type Delphi survey in two rounds was conducted to establish a comprehensive list of critical success factors of PPP power projects. Using purposive and snowball sampling techniques, experts were targeted for the Delphi survey. Mean score ranking, Cronbach’s alpha coefficient and Kendall’s concordance were used for analysis.

From the list of 37 critical success factors, 9 CSFs were deemed to be extremely significant. The five topmost CSFs were as follows: shared authority, trust and communication between public and private sectors; necessity of power project; debt guarantee to enable private partner to raise funds from the local or international financial markets; appropriate risk allocation and risk sharing; and thorough and realistic assessment of cost, projections and benefits.

The CSFs identified and prioritized in this study have the propensity to trigger policy development towards the PPP power sector in Ghana and developing countries that shares similar context. This is because the study has wide implications for financing, politics, procurement, regulations, legal and capacity building.

This study aims to understand the reasons for individuals switching from traditional banks to Internet-only banks and examine how switching intentions differ between Generation X and Generation Z. Notably, Generation Z, being digital natives, exhibits distinct characteristics compared to Generation X, who often referred to as digital immigrants. Given the technology-driven nature of Internet-only banks, a multi-group analysis between these two generations was conducted.

This study utilizes Bansal’s push–pull–mooring model as a framework to analyze switching intention. The study collected survey data from 383 Korean participants, consisting of 198 participants from Generation Z and 185 participants from Generation X.

The findings indicate that low satisfaction and discomfort are factors that push people to leave traditional banks. Specifically, Generation Z shows a significantly higher inclination to leave traditional banks due to discomfort. On the other hand, relative advantage, compatibility, observability and trialability are factors that pull people to switch to Internet-only banks. Generation X is more likely to consider adopting Internet-only banks when compatibility is high and complexity is low.

This study is the first to explore unique motivators for Generation Z, such as their discomfort with interpersonal interactions in the retail banking sector. These findings challenge earlier research emphasizing human interaction’s importance in technology adoption, offering insights into their future adoption of contactless services.

The purpose of this study is designed to achieve the learning process in producing studies involving economic issues and scenarios in business management in Malaysia. In addition, this study will provide exposure to the integration of managerial skills by using both microeconomics and macroeconomics concepts and theories to aid decision-making in a business environment.

The research method comprised qualitative methodology of literature review, case study and quantitative methodology of multiple linear regression (MLR). In this case, seven microeconomics and macroeconomics factors which are believed to significantly affect house price index (HPI) are taken into consideration which includes gross domestic product, consumer price index (CPI), government tax and subsidy on housing, overnight policy rate, unemployment rate (UNEMP), the median income (INC) and cost of production index.

This research has resulted in three significant factors affecting HPI from MLR, which include CPI, UNEMP and INC where the increase of these factors will cause a high increment of HPI. The other four factors are not significant.

Malaysia has been facing the stagnancy in house market these recent years due to issues such as massive oversupply, impacting Malaysia’s economy specifically focusing on domestic direct investment. To avoid oversupply issues, the vitality of future house demand and pricing forecast should be comprehended by involved bodies for more effective planning for the house development industry. To make a better and bigger impact, this research is intended to analyse the microeconomic and macroeconomic factors affecting the HPI to better understand the significance of each of these factors to the changes of HPI to resolve these economic issues.