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This study investigates how asset specificity, relational governance and firm adaptability relate with supply chain integration (SCI), considering selected food processing firms (FPFs) in Uganda.

This study applies a quantitative research methodology. This research draws on a sample of 103 FPFs that have been selected from a population of 345 FPFs located in Kampala district. Hypothesis testing was done using Smart PLS version 3.

Asset specificity has a significant positive relationship with SCI, and firm adaptability partially mediates this relationship. Also, there is a full mediation impact of firm adaptability on the relationship between relational governance and SCI.

This study focused on perceptual measures to get responses from managers on the level of integration with key suppliers and customers, yet firms deal with a number of suppliers and customers.

This study contributes to existing literature on SCI by applying the transaction cost theory. The study focuses on the influence of asset specificity, relational governance and firm adaptability on SCI in the food processing sector. Literature on relational governance in supply chain using the transaction cost theory remains scanty. Few studies have also focused on firm adaptability as a mediator in the FPS with specific focus on Uganda, yet the sector is highly faced with uncertain events. The uncertain events in the sector and in developing countries call for adaptive strategies. Additionally, this study is the first to use firm adaptability to mediate the influence of asset specificity and relational governance on SCI more so in a developing country like Uganda where the FPS is one of the most important in the economy.

The purpose of the current research is to present an explanatory framework for how people selectively attend to privacy-related news information about LBA depending on the extent to which they know about LBA already as well as their appraisals of privacy threats and efficacy.

The proposed model was tested using structural equation modeling based on a total of 522 useable responses obtained from an online survey.

The results revealed two different approaches to information exposure: (1) people choose to seek out privacy-related news articles when their persuasion knowledge and perceived threat level are high, whereas (2) they tend to avoid such information when perceived threats accompany fear as well as psychological discomfort, or when they believe that they are knowledgeable about LBA practices and highly capable of protecting their privacy.

With the development of real-time location-tracking technologies, the practice of LBA is becoming increasingly popular. As such, however, concerns about data collection and privacy are also on the rise, garnering a great deal of media attention. Despite the importance and constant stream of news reports on the subject, a comprehensive understanding of consumers' privacy assessments and information consumption remains underexamined. By incorporating the persuasion knowledge model and extended parallel process model, the current research presents an explanatory framework for consumers' privacy perceptions and information choice.

This study aims to examine the existing literature on sleep-related interventions and confirm the intervention methods and their effectiveness led by occupational therapists.

All the relevant literature published from 2010 to June 31, 2022, in five prominent databases were searched using the five-stage review framework proposed by Arksey and O’Malley.

In this review, four types of sleep-related interventions were led by occupational therapists (tool use, exercise program, sleep education and occupational-based program). When the intervention was analyzed based on its content, occupational therapists demonstrated excellent ability in interventions based on sensory intervention and lifestyle redesign.

Various factors cause sleep problems; hence, the development of individualized and extensive occupational therapy intervention methods is required.

There is growing interest around the world in more effectively linking public payments to the provision of public goods from agriculture. However, published evidence syntheses suggest mixed, weak or uncertain evidence for many agri-environment scheme options. To inform any future “public money for public goods” based policy, further synthesis work is needed to assess the evidence-base for the full range of interventions currently funded under agri-environment schemes. Further empirical research and trials should then focus on interventions for which there is mixed or limited evidence. Furthermore, to ensure the data collected is comparable and can be synthesised effectively, it is necessary to reach agreement on essential variables and methods that can be prioritised by those conducting research and monitoring. Future policy could then prioritise public money for the public goods that can most reliably be delivered, offering better value for taxpayers and improving the provision of ecosystem services from agricultural landscapes.

The ongoing paradigm shift in the energy sector holds paramount implications for the realization of the sustainable development goals, encompassing critical domains such as resource optimization, environmental stewardship and workforce opportunities. Concurrently, this transformative trajectory within the power sector possesses a dual-edged nature; it may ameliorate certain challenges while accentuating others. In light of the burgeoning research stream on open innovation, this study aims to examine the intricate dynamics of knowledge-based industry-university-research networking, with an overarching objective to elucidate and calibrate the equilibrium of ambidextrous innovation within power systems.

The authors scrutinize the role of different innovation organizations in three innovation models: ambidextrous, exploitative and exploratory, and use a multiobjective decision analysis method-entropy weight TOPSIS. The research was conducted within the sphere of the power industry, and the authors mined data from the widely used PatSnap database.

Results show that the breadth of knowledge search and the strength of an organization’s direct relationships are crucial for ambidextrous innovation, with research institutions having the highest impact. In contrast, for exploitative innovation, depth of knowledge search, the number of R&D patents and the number of innovative products are paramount, with universities playing the most significant role. For exploratory innovation, the depth of knowledge search and the quality of two-mode network relations are vital, with research institutions yielding the best effect. Regional analysis reveals Beijing as the primary hub for ambidextrous and exploratory innovation organizations, while Jiangsu leads for exploitative innovation.

The study offers valuable implications to cope with the dynamic state of ambidextrous innovation performance of the entire power system. In light of the findings, the dynamic state of ambidextrous innovation performance within the power system can be adeptly managed. By emphasizing a balance between exploratory and exploitative strategies, stakeholders are better positioned to respond to evolving challenges and opportunities. Thus, the study offers pivotal guidance to ensure sustained adaptability and growth in the power sector’s innovation landscape.

The primary originality is to extend and refine the theoretical understanding of ambidextrous innovation within power systems. By integrating several theoretical frameworks, including social network theory, knowledge-based theory and resource-based theory, the authors enrich the theoretical landscape of power system ambidextrous innovation. Also, this inclusive examination of two-mode network structures, including the interplay between knowledge and cooperation networks, unveils the intricate interdependencies between these networks and the ambidextrous innovation of power systems. This approach significantly widens the theoretical parameters of innovation network research.

People with autism and their families struggle with travel because of its complexity. This study aims to promote travel participation by exploring the travel needs and patterns of people with autism and their families.

A total of 28 participants were interviewed. Data were analyzed via constructivist grounded theory.

People with autism and their families displayed five travel patterns: mutual support, relatives’ visitation, independent travel, expanded socialization and package tours. These patterns were adopted in a stepwise fashion as the autistic individuals’ abilities improved. The travel challenges and support needs of Chinese autistic people and their families were identified.

The findings can inform accessibility tourism, promote an understanding of autistic people’s tourism activities among the public and industry marketers and offer strategic guidance about family travel for this population.

This effort responds to a call to investigate disability-related issues. The study evaluated the travel behavior of people with autism and their families, from a developmental perspective, presenting a new angle in research on accessibility tourism.

This study aims to objectively synthesize the volume of accounting literature on financial statement fraud (FSF) using a systematic literature review research method (SLRRM). This paper analyzes the vast FSF literature based on inclusion and exclusion criteria. These criteria filter articles that are present in the accounting fraud domain and are published in peer-reviewed quality journals based on Australian Business Deans Council (ABDC) journal ranking. Lastly, a reverse search, analyzing the articles' abstracts, further narrows the search to 88 peer-reviewed articles. After examining these 88 articles, the results imply that the current literature is shifting from traditional statistical approaches towards computational methods, specifically machine learning (ML), for predicting and detecting FSF. This evolution of the literature is influenced by the impact of micro and macro variables on FSF and the inadequacy of audit procedures to detect red flags of fraud. The findings also concluded that A* peer-reviewed journals accepted articles that showed a complete picture of performance measures of computational techniques in their results. Therefore, this paper contributes to the literature by providing insights to researchers about why ML articles on fraud do not make it to top accounting journals and which computational techniques are the best algorithms for predicting and detecting FSF.

This paper chronicles the cluster of narratives surrounding the inadequacy of current accounting and auditing practices in preventing and detecting Financial Statement Fraud. The primary objective of this study is to objectively synthesize the volume of accounting literature on financial statement fraud. More specifically, this study will conduct a systematic literature review (SLR) to examine the evolution of financial statement fraud research and the emergence of new computational techniques to detect fraud in the accounting and finance literature.

The storyline of this study illustrates how the literature has evolved from conventional fraud detection mechanisms to computational techniques such as artificial intelligence (AI) and machine learning (ML). The findings also concluded that A* peer-reviewed journals accepted articles that showed a complete picture of performance measures of computational techniques in their results. Therefore, this paper contributes to the literature by providing insights to researchers about why ML articles on fraud do not make it to top accounting journals and which computational techniques are the best algorithms for predicting and detecting FSF.

This paper contributes to the literature by providing insights to researchers about why the evolution of accounting fraud literature from traditional statistical methods to machine learning algorithms in fraud detection and prediction.

The purpose of this study is to explore the transient characteristics of mixed-flow pumps during startup process.

This study uses a full-flow field transient calculation method of mixed-flow pump based on a closed-loop model.

The findings show the hydraulic losses and internal flow characteristics of the piping system during the start-up process.

Large computational cost.

Improve the accuracy of current numerical simulation results in transient process of mixed-flow pump.

Simplify the setting of boundary conditions in the transient calculation.

Urban areas, especially in the coastal region of Bangladesh, face environmental degradation due to rapid urbanization, uncontrolled socio-economic activities and experiencing the adverse impacts of climate change. Nature-based solutions (NbS) as options for restoring, preserving, maintaining and elevating natural features or systems are becoming popular for reducing vulnerabilities caused either by natural hazards or human-induced activities. With this understanding, this study aims to explore the need of practicing NbS by studying the condition of a tidal canal (known as Thakurani Khal) and its peripheral areas of Mongla Port Municipality, a coastal and seaport town in Bangladesh.

This case study-based research uses multiple inquiries, including focus group discussions, pair-wise comparison, observation, GIS-based mapping, key informant interviews and secondary climate data review, to understand the spatial development of the area and community reactions to the changes in the urban environment.

The natural water flow of this canal is controlled by sluice gates that indirectly allowed the dweller to encroach its lands and convert the canal into a solid waste dumping area. These human-induced activities as well as the climate change-induced events (i.e. extreme heat, intensive and irregular rainfall, increased number of cyclones, etc.) have made the adjacent areas prone to waterlogging and drainage congestion. In this context, the revival of the original natural quality of the canal has been identified as an alternative to ensuring an adaptive urban environment.

This research highlights the importance of practicing NbS for developing urban resilience in the context of climate change.