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The adoption and usage of information and communication technology (ICT) has introduced transformation in the tourism arena with ICT applications extensively used in tourism industry. In addition to ICT, an advanced infrastructure is essential for the development of tourism industry. Thus, the goal of present research is to probe the impact of ICT and infrastructure on tourism development (TD) in 28 Asian economies using method of moments panel quantile regression (MM-QR) model introduced by Machado and Silva (2019) applied to a panel data from 2008 to 2020. Empirical findings demonstrate that there is an asymmetric non-linear effect of ICT and infrastructure through all quantile range. This indicates that ICT has negative effect on TD in poor countries while positive impact in rich countries. Negative impact in poor countries may be due to higher establishment cost and information technology (IT) productivity paradox. However, results confirm the importance of ICT and infrastructure in endorsing the development of tourism sector in Asian nations by lessening time and money costs and facilitating travelers.

The purpose of this study is to explore the complex interplay between technology, personal norms and emotional factors in shaping the sustainable housing choices of millennials in emerging economies. It integrates the model of goal-directed behavior, technology acceptance model and norm activation model, incorporating both self-interest and prosocial motivations. Key adaptations involve replacing perceived behavioral control with financial self-efficacy and substituting hedonic motivation for anticipated positive emotions. Moreover, it introduces location as a practical anchor.

A quantitative, cross-sectional and descriptive research design was used in this study. Data were gathered from a sample of 610 millennial residential real estate investors across Indian smart cities. A multistage stratified sampling technique was used to ensure a representative sample. For data analysis, partial least squares structural equation modeling was used. The analysis focused on hypothesis testing to examine the relationships between the constructs of interest. Bootstrap t-values and effect sizes were used to assess the significance and magnitude of these relationships, respectively.

One of the key findings of this study was the establishment of significant positive relationships between awareness of consequences, ascription of responsibility and personal norms with behavioral intentions. This underscored the importance of personal ethical considerations in shaping intentions. Perceived usefulness and ease of use were found to significantly influence attitudes positively, highlighting the relevance of these factors in forming favorable attitudes toward behaviors. Attitude, subjective norms, financial self-efficacy and location played significant positive roles. However, negative anticipated emotions decreased desire. This illustrated the complex role emotions play in motivational processes. The study also revealed that subjective norms did not significantly contribute to shaping personal norms. This indicated a potential decoupling of societal expectations from personal ethical obligations in the decision-making process.

This study offers actionable insights for both policymakers and real estate developers. For policymakers, the findings highlight the need to craft initiatives that go beyond mere awareness, instead fostering a deep sense of personal responsibility and environmental stewardship among potential homebuyers. For real estate developers, the emphasis on financial self-efficacy and location suggests a strategy shift toward designing sustainable homes that not only meet environmental standards but also align with buyers’ financial confidence and geographic preferences. Together, these strategies can drive a more widespread adoption of sustainable housing, making sustainability a tangible and appealing choice for millennials.

To the best of the authors’ knowledge, this empirical research study was one of the first studies that contributed to the literature by integrating the model of goal-directed behavior, technology acceptance model and norm activation model. This study thus offered a nuanced understanding of the interplay between normative influences, usability perceptions, ethical considerations and emotions in the context of behavioral intentions.

This paper aims to examine the financial outcome of reverse logistics among firms in a developing country. The authors draw on the organizational information processing theory to propose that analytics capability moderates the relationship between reverse logistics and financial performance.

The authors collected firm-level survey data from 200 manufacturing firms in Ghana, a developing country in sub-Saharan Africa. Partial least squares structural equations modeling is used to examine the proposed relationships, and the moderating effects are further probed using Hayes PROCESS.

The empirical results show that reverse logistics is negatively related to financial performance. However, analytics capability attenuates this negative relationship, such that firms with high analytics capability obtain a positive relationship between reverse logistics and financial performance.

Firms in developing countries should combine their reverse logistics strategies with developing analytics capabilities that help minimize uncertainties and increase the efficient collection and use of information to reduce the cost of reverse logistics.

This paper examines how reverse logistics relates to financial performance in low-resource contexts. Beyond the novelty of the context, it explores the information processing needs of reverse logistics systems and provides empirical data to support analytics capability. This has yet to be considered in prior studies.

The Elementary and Secondary School Emergency Relief (ESSER) requires districts to deliver “evidence-based interventions” to students impacted by the pandemic. The policy has created a unique opportunity for researchers and practitioners to engage with evidence to learn how recovery interventions work and under what conditions.

This study is part of a research-practice partnership (RPP) between Guilford County Schools, AIR-CALDER, Harvard University and NWEA to understand the impacts and implementation of ESSER-funded recovery programs. We use a case analysis approach and frameworks of evidence-use and RPPs to explain how researchers and Guilford leaders engage with evidence to improve and evaluate programs.

The RPP used evidence to inform Guilford leaders’ recovery approaches and strengthened researchers’ evaluations of programs. Conditions that enabled evidence engagement included the RPP’s goals, research activities and collaborative conditions such as boundary spanning activities, team meetings, relationships and trust. We also observed factors that hindered evidence engagement, including the RPP’s nascent stage, structure and breadth of goals, rapid policy timelines and other organizational conditions in Guilford.

Given the complexities of pandemic recovery, RPPs can help researchers evaluate programs in their local context, and present evidence in ways that are actionable to guide decision-making. District leaders can play a valuable role in co-designing research studies attuned to local priorities and context and facilitating research participation among internal stakeholders. However, newly formed RPPs with broad goals for impact will need more time and resources to build an improvement infrastructure for sustaining pandemic recovery.

This research aims to investigate the disciplinary functions of depositors and subordinated debt holders within Indonesia's dual banking system, examining the impact of regulatory changes on market discipline.

The study employs a comprehensive analysis of the dual banking system in Indonesia over 15 years. Utilizing a non-public dataset from the Financial Services Authority and the Indonesia Deposit Insurance Corporation, the study employs propensity score matching and difference-in-differences analysis.

The findings reveal distinct patterns in the exercise of market discipline by depositors over different regulatory regimes. During the blanket guarantee regime (2002–2005), depositors lacked the incentive to monitor banks but resumed their disciplinary role under the limited guarantee regime (2005–2017). Islamic banks faced simultaneous market and regulatory discipline, with market discipline prevailing.

This study contributes to the literature by providing novel insights into the interplay between regulatory changes, market discipline and depositor behavior within Indonesia's dual banking system. The utilization of a comprehensive non-public dataset from regulatory authorities adds to the originality of the research.

This paper aims to explore three operations and supply chain management (OSCM) approaches for meeting the 2 °C targets to counteract climate change: adaptation (adjusting to climatic impacts); mitigation (innovating towards low-carbon practices); and carbon-removing negative emissions technologies (NETs). We suggest that adaptation nor mitigation may be enough to meet the current climate targets, thus calling for NETs, resulting in the following question: How can operations and supply chains be reconceptualized for NETs?

We draw on the sustainable supply chain and transitions discourses along with interview data involving 125 experts gathered from a broad research project focused on geoengineering and NETs. We analyze three case studies of emerging NETs (biochar, direct air carbon capture and storage and ocean alkalinity enhancement), leading to propositions on the link between OSCM and NETs.

Although some NETs are promising, there remains considerable variance and uncertainty over supply chain configurations, efficacy, social acceptability and potential risks of unintended detrimental consequences. We introduce the concept of transformative OSCM, which encompasses policy interventions to foster the emergence of new technologies in industry sectors driven by social mandates but lack clear commercial incentives.

To the best of the authors’ knowledge, this paper is among the first that studies NETs from an OSCM perspective. It suggests a pathway toward new industry structures and policy support to effectively tackle climate change through carbon removal.

The objective of this study is to reevaluate the correlation among pharmaceutical consumption, per capita income, and life expectancy across different age groups (at birth, middle age, and advanced age) within the OECD countries between 1998 and 2018.

We employ a two-step methodology, utilizing two independent approaches. Firstly, we con-duct the Dumitrescu-Hurlin pairwise panel causality test, followed by Machine Learning (ML) experiments employing the Causal Direction from Dependency (D2C) Prediction algorithm and a DeepNet process, thought to deliver robust inferences with respect to the nature, sign, direction, and significance of the causal relationships revealed in the econometric procedure.

Our findings reveal a two-way positive bidirectional causal relationship between GDP and total pharmaceutical sales per capita. This contradicts the conventional notion that health expenditures decrease with economic development due to general health improvements. Furthermore, we observe that GDP per capita positively correlates with life expectancy at birth, 40, and 60, consistently generating positive and statistically significant predictive values. Nonetheless, the value generated by the input life expectancy at 60 on the target income per capita is negative (−61.89%), shedding light on the asymmetric and nonlinear nature of this nexus. Finally, pharmaceutical sales per capita improve life expectancy at birth, 40, and 60, with higher magnitudes compared to those generated by the income input.

These results offer valuable insights into the intricate dynamics between economic development, pharmaceutical consumption, and life expectancy, providing important implications for health policy formulation.

Very few studies shed light on the nature and the direction of the causal relationships that operate among these indicators. Exiting from the standard procedures of cross-country regressions and panel estimations, the present manuscript strives to promote the relevance of using causality tests and Machine Learning (ML) methods on this topic. Therefore, this paper seeks to contribute to the literature in three important ways. First, this is the first study analyzing the long-run interactions among pharmaceutical consumption, per capita income, and life expectancy for the Organization for Economic Co-operation and Development (OECD) area. Second, this research contrasts with previous ones as it employs a complete causality testing framework able to depict causality flows among multiple variables (Dumitrescu-Hurlin causality tests). Third, this study displays a last competitive edge as the panel data procedures are complemented with an advanced data testing method derived from AI. Indeed, using an ML experiment (i.e. Causal Direction from Dependency, D2C and algorithm) it is believed to deliver robust inferences regarding the nature and the direction of the causality. All in all, the present paper is believed to represent a fruitful methodological research orientation. Coupled with accurate data, this seeks to complement the literature with novel evidence and inclusive knowledge on this topic. Finally, to bring accurate results, data cover the most recent and available period for 22 OECD countries: from 1998 to 2018.

The numerous spoil grounds brought about by mega transportation infrastructure projects which can be influenced by the ecological environment. To achieve better management of spoil grounds, this paper aims to assess their comprehensive risk levels and categorize them into different categories based on ecological environmental risks.

Based on analysis of the environmental characteristics of spoil grounds, this paper first comprehensively identified the ecological environmental risk factors and developed a risk assessment index system to quantitatively describe the comprehensive risk levels. Second, this paper proposed a comprehensive model to determine the risk assessment and categorization of spoil ground group in mega projects integrating improved projection pursuit clustering (PPC) method and K-means clustering algorithm. Finally, a case study of a spoil ground group (includes 50 spoil grounds) in a mega infrastructure project in western China is presented to demonstrate and validate the proposed method.

The results show that our proposed comprehensive model can efficiently assess and categorize the spoil grounds in the group based on their comprehensive ecological environmental risk. In addition, during the process of risk assessment and categorization of spoil grounds, it is necessary to distinguish between sensitive factors and nonsensitive factors. The differences between different categories of spoil grounds can be recognized based on nonsensitive factors, and high-risk spoil grounds which need to be focused more on can be identified according to sensitive factors.

This paper develops a comprehensive model of risk assessment and categorization of a group of spoil grounds based on their ecological environmental risks, which can provide a reference for the management of spoil grounds in mega projects.

This systematic literature review paper critically examines the effectiveness of screencast feedback compared with text feedback in promoting student learning outcomes in online higher education. This paper aims to contribute to the ongoing discussion surrounding feedback modalities and their impact on online learning environments.

This paper adopts a systematic review approach to synthesise and analyse existing studies investigating the use of screencast feedback in online higher education settings. A comprehensive search and selection process was employed to identify relevant literature. The selected studies were then analysed for their methodologies, findings and implications. This paper seeks to provide an overview of the current state of research, highlighting the benefits, challenges and potential impacts of screencast feedback on student learning outcomes.

The findings of this paper suggest that while there is a positive perception of screencast feedback among students and instructors, drawing definitive conclusions about its superiority over text feedback remains at the very beginning. Students generally appreciate the personalised, supportive and engaging nature of screencast feedback, particularly within the online learning context. However, challenges such as technical barriers and potential workload implications for instructors are also noted. Further empirical research is needed to comprehensively evaluate the comparative efficacy of screencast feedback, considering factors like online engagement, digital literacy and the impact on diverse student populations.

This review underscores the acute necessity for expansive and meticulously designed studies that can provide conclusive insights into the authentic potential of screencast feedback and its resonance within the unique landscape of online learning. Through rigorous inquiry, educators can discern the optimal strategies for harnessing the advantages of screencast feedback to enhance student learning outcomes, aligning harmoniously with the dynamics of virtual classrooms.

Screencast feedback emerges as a promising avenue to foster meaningful connections between instructors and learners. The review highlights that screencast feedback engenders a more dialogic interaction between lecturers and students, resulting in personalised, supportive and engaging feedback experiences.

The systematic review conducted underscores the positive reception of screencast feedback from both students and lecturers in this context. The findings are consistent with the principles of social constructivist theory, suggesting that the interactive and personalised nature of screencast feedback facilitates a richer educational experience for students, even within the confines of virtual classrooms (Vygotsky, 1978).

This innovative blend of methodologies contributes new insights that can inform educational practices and pedagogical strategies in online learning environments.

Talent management is conducted to maximize an organization's overall performance and efficiency which helps to serve as a competitive advantage. Human resource management is a concept which includes human-related activities, but talent management is a strategy which helps to get new talent, develop their skill sets and provide better employee engagement and experience to retain the top potential employees in an organization. Improvement in recruiting and retention of a workforce results from a well-executed talent acquisition approach. In the 21st century, employee retention has become a primary concern for the organizations specially with work from home and hybrid models.

The workforce for tomorrow is going to be very different from what it has been. Technology is transforming the way people work within organizations. The workplace is rapidly evolving in terms of people and processes and is going through a lot of technological changes. The terminologies such as automation, artificial intelligence, augmented reality and block chain technologies are slowly becoming part of the workplace and everyday activities of the organization.

The challenges are many and especially post-pandemic organizations are going through some major changes such as a mindset shift of employees to take up more remote working opportunities, building virtual teams, increase in the gig economy workers (contractual workers) and a diverse workforce which makes it even more challenging for the organization to manage and retain talent.