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This study aims to explore the strengths, weaknesses, opportunities and threats (SWOT) of the Muslim-friendly homestay business in Malaysia to help identify and recommend practical strategies to capitalize on the strengths and potentials while overcoming the current shortcomings and threats.

The Muslim-friendly business owner and operators in Sabah, Malaysia, were the subject of a series of focus groups and expert opinion interviews. The data was transcribed, and then the variables were categorized into the four SWOT categories using content and thematic analysis. Meanwhile, threats, opportunities, weaknesses and strengths (TOWS) analysis is used to identify the best strategy alternatives.

The SWOT analysis identifies several strengths (e.g. diverse and unique Islamic culture and heritage [S1], iconic Islamic landmarks [S2], rich natural beauty [S3], well-established halal tourism industry [S4]); weaknesses (e.g. limited awareness [W1], limited infrastructure and facilities [W2], limited human resources and trained personnel [W3], lack of Islamic tourism products and experiences [W4]); opportunities (e.g. growing demand for Islamic tourism [O1], increasing disposable income [O2], potential for collaborations [O3], potential for partnerships [O4], potential for expanding Sabah’s halal tourism offerings [O5]); and threats (e.g. competition [T1], political instability [T2], economic downturns [T3] and environmental and social challenges [T4]).

This paper could serve as a guideline and supplementary information for stakeholders in the homestay industry to grasp their business environment better.

To the best of the authors’ knowledge, this is the first study of its type to blend SWOT and TOWS analysis with the sector of Muslim-friendly homestays. Hence, the findings might expand understanding of the Muslim-friendly homestays industry and aid businesses in penetrating this growing market.

This paper proposes a progressive, multi-level framework for diagnosing maintenance performance: rapid performance health checks of key performance for different equipment groups and end-to-end process diagnostics to further locate potential performance issues. A question-based performance evaluation approach is introduced to support the selection and derivation of case-specific indicators based on diagnostic aspects.

The case research method is used to develop the proposed framework. The generic parts of the framework are built on existing maintenance performance measurement theories through a literature review. In the case study, empirical maintenance data of 196 emergency shutdown valves (ESDVs) are collected over a two-year period to support the development and validation of the proposed approach.

To improve processes, companies need a separate performance measurement structure. This paper suggests a hierarchical model in four layers (objective, domain, aspect and performance measurement) to facilitate the selection and derivation of indicators, which could potentially reduce management complexity and help prioritize continuous performance improvement. Examples of new indicators are derived from a case study that includes 196 ESDVs at an offshore oil and gas production plant.

Methodological approaches to deriving various performance indicators have rarely been addressed in the maintenance field. The proposed diagnostic framework provides a structured way to identify and locate process performance issues by creating indicators that can bridge generic evaluation aspects and maintenance data. The framework is highly adaptive as data availability functions are used as inputs to generate indicators instead of passively filtering out non-applicable existing indicators.

It is widely evident that trust and commitment are important pillars for strengthening the relationship between financial service firms and their customers. However, it has not been explored how the service quality, perceived cost and role of agents are important for financial service firms. To overcome this gap, this study aims to investigate the role of service quality, perceived cost and the role of agents as the commitment–trust factors in the financial insurance service (Takaful) in Malaysia, enhancing customer satisfaction.

The study follows a quantitative design in which primary data was collected using a survey instrument. The measurement instrument was adapted from the previous research, and data were collected from 264 customers of the Takaful financial service organizations in Malaysia. The data were analyzed using variance-based structural equational modeling in Smart-PLS software.

This research has revealed several useful insights that demonstrate a significant impact on service quality, perceived cost and the agents’ role in forging close relationships with their customers. Corporate image has a moderating role in relationships and has significantly impacted takaful insurance companies. The results imply that regardless of the corporate image of the financial service organizations, customers are concerned about the prices and the quality of the agents’ services.

In this study, only the predictors such as service quality, perceived costs and agents’ roles as trust–commitment factors were examined to determine customer satisfaction. Other investigations are highly recommended, such as value co-creation in takaful, takaful customer experience and takaful trust. This study offers insights to takaful insurance companies on how to keep up a positive corporate image, which will boost their trust–commitment factors and ultimately increase customer satisfaction.

By presenting commitment–trust factors and company image in an identifiable framework, the current study has expanded the discussion on takaful financial insurance services. The methodology is developed and rigorously tested to gauge customer satisfaction in takaful financial service organizations’ context.

This study aims to know the tactician role of financial technology (FinTech) in the field of accounting and auditing through contextualized systematic literature review by using bibliometric analysis.

The qualitative bibliometric analysis includes studies from 2017 to 2021 using the Scopus and Web of Science databases, which yielded 277 published papers with the keywords, FinTech accounting and auditing. The contextualized systematic literature review greatly helped in clarifying the content within each cluster.

The study identified the tactician role of fintech primarily in the accounting and auditing professional field. Fintech is still in its inception, with continual development and implementation taking place especially, in the auditing field. The findings also confirm that FinTech can produce a confluence between various research areas, including accounting, auditing, business finance, economics, management and business field.

The study describes the tactician role of FinTech and its huge possibility for future study in the accounting and auditing field among professionals, academics and regulators.

This study be able to help accounting professionals, policymakers and government regulators to establish policy development, as this research emphasizes the tactician role of FinTech in the accounting and auditing field.

FinTech in accounting and auditing might add to the existing field of FinTech in the IR4.0 era that give benefits to different players such as policymakers, governments, researchers, FinTech entrepreneurs and practicing professionals.

To the best of the author’s knowledge, little focus has been given about FinTech in the accounting and auditing field using bibliometric analysis. The insights of systematic literature review provide researchers on FinTech among practicing professionals and offer opportunities for further scientific endeavours.

This study provides theoretical and empirical insights into how firms can enhance their performance strategically and financially by integrating learning and transformational capabilities into research and development (R&D) activities based on the dynamic capabilities approach. To achieve this, the authors propose that transformational capabilities in R&D mediate the relationship between learning capabilities in R&D and competitive advantage.

Using a purposive sampling technique and standardized questionnaires, data were collected from 118 R&D and senior managers. To analyze the data, multiple regression analysis, along with SPSS PROCESS macro (Model 4), was used.

The results support the theoretical assumption that there are direct and indirect positive and significant effects between learning capabilities in R&D and competitive advantage as mediated by transformational R&D capabilities.

This study explores R&D from a dynamic capabilities perspective and suggests that learning capabilities should come first to enhance businesses’ competitive advantage. Furthermore, transformational R&D capabilities can explain the relationship between learning capabilities in R&D and competitive advantage. The authors recommend that researchers should investigate the contributions of R&D to promote competitive advantage.

GraphQL is a new Open API specification that allows clients to send queries and obtain data flexibly according to their needs. However, a high-complexity GraphQL query may lead to an excessive data volume of the query result, which causes problems such as resource overload of the API server. Therefore, this paper aims to address this issue by predicting the response data volume of a GraphQL query statement.

This paper proposes a GraphQL response data volume prediction approach based on Code2Vec and AutoML. First, a GraphQL query statement is transformed into a path collection of an abstract syntax tree based on the idea of Code2Vec, and then the query is aggregated into a vector with the fixed length. Finally, the response result data volume is predicted by a fully connected neural network. To further improve the prediction accuracy, the prediction results of embedded features are combined with the field features and summary features of the query statement to predict the final response data volume by the AutoML model.

Experiments on two public GraphQL API data sets, GitHub and Yelp, show that the accuracy of the proposed approach is 15.85% and 50.31% higher than existing GraphQL response volume prediction approaches based on machine learning techniques, respectively.

This paper proposes an approach that combines Code2Vec and AutoML for GraphQL query response data volume prediction with higher accuracy.

The purpose of this study is to examine the effects of inclination angle on the thermal energy storage capability of a phase change material (PCM) within a disc-shaped container. Different container materials are also tested such as plexiglass and aluminium. This study aims to assess the energy storage capacity, melting behaviour and temperature distributions of PCM with a specific melting range (22°C–26°C) for various governing parameters such as inclination angles, aspect ratios (AR) and temperature differences (ΔT) and compare the melting behaviour and energy storage performance of PCM in aluminium containers to those in plexiglass containers.

A finite volume approach was adopted to evaluate the thermal energy storage capability of PCMs. Five inclination angles ranging from 0° to 180° were considered and the energy storage capacity. Also, the melting behaviour of the PCM and temperature distributions of the container with different materials were tested. Two different AR and ΔT values were chosen as parameters to analyse for their effects on the melting performance of the PCM. Conjugate heat transfer problem is solved to see the effects of conduction mode of heat transfer.

The results of the study indicate that as AR decreases, the effect of the inclination angles on the energy storage capacity of the PCM decreases. For lower ΔT, the difference between the maximum and minimum stored energies was 20.88% for AR = 0.20, whereas it was 6.85% for AR = 0.15. Furthermore, under the same conditions, the PCM stored 8.02% more energy in plexiglass containers than in aluminium containers.

This study contributes to the understanding of the influence of inclination angle, container material, AR and ΔT on the thermal energy storage capabilities of PCM in a novel designed container. The findings highlight the importance of AR in mitigating the effect of the inclination angle on energy storage capacity. Additionally, comparing aluminium and plexiglass containers provides insights into the effect of container material on the melting behaviour and energy storage properties of PCM.

This paper investigated the organizational adoption of big data analytics (BDA) in the context of supply chain planning (SCP) to conceptualize how resources are orchestrated for organizational BDA adoption and to elucidate how resources and capabilities intervene with the resource management process during BDA adoption.

This research elaborated on the resource orchestration theory and technology innovation adoption literature to shed light on BDA adoption with multiple case studies.

A framework for the resource orchestration process in BDA adoption is presented. The authors associated the development and deployment of relevant individual, technological and organizational resources and capabilities with the phases of organizational BDA adoption and implementation. The authors highlighted that organizational BDA adoption can be initiated before consolidating the full resource portfolio. Resource acquisition, capability development and internalization of competences can take place alongside BDA adoption through structured processes and governance mechanisms.

A relevant discussion identifying the capability gap and provides insight into potential paths of organizational BDA adoption is presented.

The authors call for attention from policymakers and academics to reflect on the changes in the expected capabilities of supply chain planners to facilitate industry-wide BDA transition.

This study opens the black box of organizational BDA adoption by emphasizing and scrutinizing the role of resource management actions.

The COVID-19 pandemic is not a foodborne infectious disease, but it has dramatically impacted food safety practices worldwide due to its potential for transmission through contaminated surfaces and food. Accordingly, the Omicron variant seems to have affected food-related activities and behaviours and disturbed food supply networks since its appearance in November 2021. Hence, this paper aims to assess how the Omicron variant impacted food safety knowledge, attitudes and practices amongst adult consumers in five countries: Bosnia and Herzegovina, North Macedonia, Serbia, Montenegro and Russia.

The study is based on an online survey. The questionnaire was developed and revised based on previous research on the impact of previous COVID-19 waves on food-related activities in several countries. The questionnaire was distributed through the SurveyMonkey platform from January 15 to February 25, 2022. It consisted of 29 multiple-choice and one-option questions organised into three sections. A total of 6,483 valid responses were received. Statistical Package for Social Sciences (SPSS) version 25.0 was used to analyse the survey results.

According to the survey findings, food safety practices evolved during the Omicron wave in the studied countries. Firstly, less than half of the sample used a face mask whilst purchasing food. Secondly, regarding food safety knowledge, the survey results suggest that there is still a lack of knowledge in the studied countries. Thirdly, the survey indicates a lack of knowledge amongst the respondents regarding food safety attitudes. For instance, more than a third of the sample (34.4%) are unsure whether the COVID-19 virus can be transmitted through food. These results are surprising and alarming, especially considering that our sample has a higher education than the population of the studied countries.

The main limitation of this research is the sample bias. Survey participants were randomly chosen, enrolled voluntarily and not rewarded. As a result, the questionnaire was self-administered and completed exclusively by people motivated by an interest in the topic. Consequently, our survey does not represent the general population of the studied countries. People with a high degree of education and women, for example, were overrepresented in our sample.

This study is unique in that it is the first to gather information and analyse people’s perceptions of the effects of the Omicron variant on food safety. As a result, the findings of this survey offer a solid basis for future investigations into the impact of the pandemic on food safety in the Balkan region and Russia. This study can help further understand the changes during the COVID-19 pandemic. It provides crucial insights that can be used to guide future decision-making and policy development regarding improving food safety practices. This and other future studies will be a foundation for organisational and government readiness for future shocks, crises and pandemics. The effects of the present Ukrainian conflict on agricultural systems and supply chains throughout the globe (e.g. increased food prices) show that this is timely, urgent and highly required.

Rapid changes in the global environment and the effects of existing economic issues triggered by COVID-19 and the war in Ukraine have posed several challenges for manufacturing firms. A hybrid strategy integrating lean and agile (leagile) systems is viable for firms to enhance their capabilities in such dynamic contexts. This paper examines the critical drivers of leagile manufacturing system adoption in an emerging economy from the technological, organizational and environmental (TOE) perspective.

A cross-sectional survey is carried out to obtain data from 438 managers working in 219 manufacturing firms. Multiple regression analysis is applied to test the effect of technological, organizational and environmental drivers on the adoption of leagile systems.

The results show that organization capacity, environmental uncertainty and relative advantage demonstrate the most significant positive relationships with the leagile systems adoption wherein complexity and resistance to change appear to exhibit significant negative associations. Unexpectedly, firm size unveils no significant effect on the adoption of leagile systems.

To deal effectively with critical challenges triggered by ever-changing environment, firms have sought to adopt innovative systems for achieving products' availability in the markets at the right quality and price. A hybrid strategy integrating lean and agile (leagile) systems is viable to enhance a firm's capabilities in such dynamic contexts. The findings of our study help top management and policymakers identify and assess the critical drivers that may facilitate or hinder the successful adoption of leagile systems.

A major trend of studies in the field of manufacturing systems has focused on the critical success factors of adopting either lean or agile systems. Furthermore, research work concerning leagile as a hybrid system focuses primarily on the conceptual development rather than empirical grounds of leagile systems. Given the lack of empirical research in this field, this study offers an early attempt to predict leagile system adoption in an emerging economy. It also contributes to the manufacturing systems research by extending the extant knowledge about the role of firm-level drivers in leagile system adoption from the TOE perspective.