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The aim of this research work is to examine the originator which is affecting in Thailand the adoption of m-commerce (based on the behavioural intention). The usage of m-commerce has faced reluctance by the subscribers of mobile phone, which is in general the most anticipated challenge among both the developing and developed countries. Similarly, there are restricted empirical research work regarding to the m-commerce in Thailand. As a result, in the situation of developing countries (for instance, Thailand specially), very less numbers of research exist for the recognition of important variables for the m-commerce installation or estimating the m-commerce adoption variables. For explaining the behavioural targets of subscribers and for estimation generally the model that has been used is referred to as technology acceptance model (TAM). First, the factor subjective norms by the region of technology acceptance had contradictory outcomes and inconsistency to the behavioural target. In this study, we employed the Smart Partial Least Square Structural Equation Modelling version 3.2.6 as a data analysis technique. The response rate of the current study is 81%. The results have certainty that has established the presence of these associations between the users which implicated the significance of subjective norms in Thailand which were recognized. The personal opinion of usefulness, perceptions of attitude and easy usage to m-commerce are the important features towards the subjective norms which are the social impacts.

The study was planned to examine the impact of subjective norms on the behavioural intentions of Thai e-banking users. Additionally, the study has also examined the mediating role of perceived usefulness of e-banking in the relationship between the subjective norms and e-banking adoption. The subjective norms construct in this study was decomposed into societal descriptive and injunctive norms, and personal descriptive and injunctive norms. It is clear from the literature review that highly inconsistent findings were reported between perceived usefulness and subjective norms because of the contradiction in the findings obtained by the researchers. This occurred may be because trivial attention was given to the relationship between subjective norm and perceived usefulness. In current research, it is argued that there are many advantages of e-banking adoption which includes mobility, convenience and 24-hour accessibility anywhere anytime with no physical limitation of location as required in old-styled e-commerce. For that reason, it is hypothesized that people who believe that these advantages would result in the improvement in their performance are expected to create a positive environment for technology adoption. In the latest quantitative research development, the partial least squares (PLS) path modelling is considered to be unsuitable in determining the validity of the model. For this purpose, a two-step process is implemented in current research. The results of the present study, argued that e-banking is adopted voluntarily and the existence of high social norms in collectivist culture greatly influences the potential adopters' attitude and behaviour by the opinions of their significant others particularly in Thai context.

The purpose of this study is to develop a novel general mathematical model to find the optimal product mix of commercial graphite products, which has a complex production process with alternative sub-processes in the graphite mining production process.

The network optimization was adopted to model the complex graphite mining production process through the optimal allocation of raw graphite, byproducts, and saleable products with comparable sub-processes, which has different processing capacities and costs. The model was tested on a selected graphite manufacturing company, and the optimal graphite product mix was determined through the selection of the optimal production process. In addition, sensitivity and scenario analyses were carried out to accommodate uncertainties and to facilitate further managerial decisions.

The selected graphite mining company mines approximately 400 metric tons of raw graphite per month to produce ten types of graphite products. According to the optimum solution obtained, the company should produce only six graphite products to maximize its total profit. In addition, the study demonstrated how to reveal optimum managerial decisions based on optimum solutions.

This study has made a significant contribution to the graphite manufacturing industry by modeling the complex graphite mining production process with a network optimization technique that has yet to be addressed at this level of detail. The sensitivity and scenario analyses support for further managerial decisions.

This study aims to minimize the transportation-related cost in distribution while utilizing a heterogeneous fixed fleet to deliver distinct demand at different geographical locations with a proper workload balancing approach. An increased cost in distribution is a major problem for many companies due to the absence of efficient planning methods to overcome operational challenges in distinct distribution networks. The problem addressed in this study is to minimize the transportation-related cost in distribution while using a heterogeneous fixed fleet to deliver distinct demand at different geographical locations with a proper workload balancing approach which has not gained the adequate attention in the literature.

This study formulated the transportation problem as a vehicle routing problem with a heterogeneous fixed fleet and workload balancing, which is a combinatorial optimization problem of the NP-hard category. The model was solved using both the simulated annealing and a genetic algorithm (GA) adopting distinct local search operators. A greedy approach has been used in generating an initial solution for both algorithms. The paired t-test has been used in selecting the best algorithm. Through a number of scenarios, the baseline conditions of the problem were further tested investigating the alternative fleet compositions of the heterogeneous fleet. Results were analyzed using analysis of variance (ANOVA) and Hsu’s MCB methods to identify the best scenario.

The solutions generated by both algorithms were subjected to the t-test, and the results revealed that the GA outperformed in solution quality in planning a heterogeneous fleet for distribution with load balancing. Through a number of scenarios, the baseline conditions of the problem were further tested investigating the alternative fleet utilization with different compositions of the heterogeneous fleet. Results were analyzed using ANOVA and Hsu’s MCB method and found that removing the lowest capacities trucks enhances the average vehicle utilization with reduced travel distance.

The developed model has considered both planning of heterogeneous fleet and the requirement of work load balancing which are very common industry needs, however, have not been addressed adequately either individually or collectively in the literature. The adopted solution methodologies to solve the NP-hard distribution problem consist of metaheuristics, statistical analysis and scenario analysis are another significant contribution. The planning of distribution operations not only addresses operational-level decision, through a scenario analysis, but also strategic-level decision has also been considered.

The planning of distribution operations not only addresses operational-level decisions, but also strategic-level decisions conducting a scenario analysis.

Achieving swift and even flow of cargo through the border, the ultimate objective of cross-border logistics (CBL) requires the close coordination and collaboration of a multitude of stakeholders, as well as optimally configured systems. To achieve and sustain competitiveness in a dynamic international trade environment, CBL processes must undergo periodic analysis, improvement and optimization. This study aims to develop a modelling framework to capture CBL processes for analysis and improvement.

Relying on the extant literature, a meta-model is developed incorporating significant perspectives required to model CBL processes. Popular process modelling notations are evaluated against the meta-model and their ease of comprehension is also evaluated. The selected notation through evalution is augmented with addendums for a comprehensive depiction of CBL processes.

The capacity of role activity diagrams (RADs) to depict all perspectives, including interactions in a single diagram, makes them particularly suitable for modelling CBL processes. RADs have been complemented with physical flow diagrams and methods to capture temporal dimension, enabling a comprehensive view of CBL processes laying the foundation for insightful analysis.

The meta-model developed in this paper paves the way to develop an analysis framework which requires further research.

The lack of well-accepted modelling notations for studying CBL processes prompts researchers to search and adapt different formalisms. This study has filled this gap by proposing a comprehensive modelling framework able to capture CBL processes at different granularities in rich detail. Not only does the developed meta-model aid in selecting the notation, it is also useful in analysing the constituent elements of CBL processes.

The purpose of the study is to mainstream the disaster risk reduction (DRR) and disaster resilience measures into the GreenSL® building rating system in Sri Lanka to demonstrate a more holistic approach in achieving sustainability with resilience.

First, a comprehensive literature review was carried out on green building practices and rating tools, natural hazards and DRR and global and local frameworks. Next, criteria were developed incorporating the disaster resilience aspects through eight expert committee meetings and included the rating tool in three levels. Finally, 11 green-certified buildings from the Green Building Council of Sri Lanka were reevaluated using the new disaster resilient GREENSL® rating system for built environment as a validation for the new tool and to analyze the new certification levels.

All the green-certified buildings in hazard-prone areas dropped their certification by one level while the buildings in nonhazard-prone areas remained in the certification after being evaluated by the new DRR-incorporated rating system, which recommends the use of new tool for the buildings in hazard-prone areas. But due to the rapid changes in climate and the unpredictable trends of natural hazards, the use of new DRR incorporated GREENSL® rating system for built environment for the certification of buildings is highly endorsed.

This is the first research study based on the GREENSL rating system. And it is the first effort to incorporate DRR aspects to any rating tool in Sri Lanka. The projects that were evaluated for the validation of the new tool are the actual projects which obtained green building certification. Also, it is apparent that this study has gone some way towards enhancing the understanding of blending the sustainability and resilience in rating systems for built environment.

This study has incorporated competitiveness by considering it a significant factor behind determining as well as moderating industrial value added in the environmental Kuznets curve (EKC) framework. This study aims to explore the moderating role of competitiveness policy in EKC with an aim to promote business led sustainability at national level.

Considering the environmental deterioration aspect of industrialization, this study tests the existence of EKC for SAARC countries using the data from 1996 to 2021 using second-generation static panel data model.

Estimated results have validated that moderating effect is responsible for improving environmental sustainability in SAARC countries. Furthermore, population density is responsible for increasing while trade openness is responsible for decreasing carbon emissions.

Higher industrial activities are a symbol of upward-moving economic growth. But its other impact is in the form of environmental deterioration. However, the relationship between industrialization and environmental quality can be identified through EKC.

This study explores the relationships among multiple factors, including growth mindset, lifelong learning and continuous professional development (CPD), influencing teachers’ integration of information and communication technology (ICT) into their teaching methods.

The study involved 1,095 Indonesian vocational high school teachers who participated in in-service or preservice teacher development programs. Data was collected through a survey, and a structural equation model with partial least squares parameter estimation was used to analyze the relationships and mediations.

Structural equation modeling revealed that a growth mindset positively affects both lifelong learning and CPD. Moreover, lifelong learning positively impacts CPD. Furthermore, all of these variables demonstrate a positive effect on teachers’ ICT integration in the classroom. The findings indicate that lifelong learning and CPD partially mediate the relationship between a growth mindset and ICT integration.

This study contributes to the literature on the determinants of teachers’ ICT usage postparticipation in in-service and preservice teacher programs. The findings underscore the significant impact of a growth mindset on teachers’ ICT use in the classroom.

The purpose of this study is to examine the impact of a recent innovation in the uranium market, the Global X Uranium Exchange-Traded Fund (URA), on the trading characteristics of constituent and non-constituent stocks.

The authors analyse bid-ask spread measures, relative effective spreads and adverse selection costs to assess changes in information asymmetry among uranium stocks. The authors also study abnormal returns to assess the impact of URA on the market.

Over a three-month period, following the introduction of URA, the authors find uranium stocks display decreased bid-ask spread measures, driven by reductions in information asymmetry. Relative effective spreads decrease by 36% after the introduction of URA, and adverse selection costs decline by 24% over the same period. Uranium stocks experience a significant positive abnormal return of 5.0% the day after the introduction of URA with subsequent price reversals. These suggest that the introduction of URA prompted uninformed traders to rebalance portfolios and migrate to the less information-sensitive Exchange-Traded Fund (ETF), causing temporary deviations in trading characteristics.

The authors demonstrate that the introduction of new financial securities to the market can have a significant impact on the trading characteristics of related equities. As URA is the only ETF in the uranium sector, the authors thereby avoid the influence of multiple ETFs that may have impacted previous studies.

This study aims to establish the effect of environmental, social and governance (ESG) practices on Australian energy and utility investment performance.

Conventional and ESG-rated portfolios are constructed using monthly returns and ESG scores of S&P/ASX 300 listed energy and utility firms from 2014 to 2022. Portfolio performance is estimated using a four-factor regression model, controlling for any economic shocks associated with the COVID-19 pandemic.

The findings show that the lower the ESG score associated with the overall ESG and environmental portfolios, the greater the performance compared to the market (but not the conventional and other ESG portfolios). High ESG scores do not appear to influence the performance of the energy and utility portfolios, which contrasts expectations that the uptake of ESG should deliver superior risk-return outcomes for investors. The findings also indicate that a contrarian investment approach may be a reasonable performance indicator for high-rated ESG portfolios. ESG practices did not impact portfolio performance during the COVID-19 pandemic.

This research has contributed to the literature by offering ESG investment insights for policymakers, regulators, fund managers and investors. Consistent with the agency perspective on ESG practices and efficient market hypothesis, the evidence implies that, regardless of ESG scores (either high or low), investors should consider investing passively in diversified energy and utility portfolios or low-cost index fund equivalents.