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To inform ways of improving valuation quality, this study seeks to understand the lived experiences of practising valuers regarding the challenges of conducting quality valuations.

This study adopts a qualitative strategy involving 19 semi-structured interviews with valuers in New Zealand. The interview data were analysed using progressive comparative analysis and the constant comparative method, which yielded comprehensive and well-founded conclusions.

The data analysis revealed several challenges that hinder the improvement and maintenance of valuation quality. These challenges were categorised into nine key areas, covering a wide range of issues, including a wide scope of practice, lack of experienced valuers, inappropriate use of graduate valuers, stakeholder expectations, access to relevant information, differing approaches, valuer attitudes and dissatisfaction with compensation.

The findings of this study have the potential to inform the valuation profession and other stakeholders about the challenges that practising valuers face in conducting quality valuations, which can ultimately lead to improvements in the valuation process.

This study contributes to the valuation literature, by highlighting the lived experiences of valuers in terms of the potential and challenges pertaining to valuation quality improvement. This has been an area that has received limited attention in the past, and an understanding of these issues has the potential to approach valuation quality in new and innovative ways.

The complexity of property valuation, coupled with valuers’ cognitive limitations, makes some degree of error inevitable in valuations. However, given the crucial role that valuations play in the efficient functioning of the economy, there is a need for continuous improvement in the reliability of reported values by enhancing the quality of the decision-making process. The purpose of this paper is to review previous research on valuation decision-making, with particular interest in examining the approaches to improving the quality of valuation decisions and identifying potential areas for further research.

The paper adopts a narrative approach to review 42 research articles that were obtained from Scopus and Web of Science databases and through author citation searches.

Our findings show that existing literature is skewed towards examining the use of technology in the form of decision support systems (DSS), with limited research attention on non-technological (i.e. behavioural) approaches to improving the quality of valuation decisions. We summarise the non-technological approaches and note that much of the discussions on these approaches often appear as recommendations arising from other studies rather than original investigations in their own rights.

We conclude that studies investigating the effectiveness of the non-technological approaches to improving valuation decision-making are lacking, providing various avenues for further research.

This paper presents the first attempt to provide a comprehensive overview of non-technological approaches to improving the quality of valuation decisions.

Supply chain risks and disruptions pose a significant threat to the healthcare industry. This paper aims to synthesize the research streams in the intersection of healthcare supply chain management and risk management to identify the research gaps and future research directions.

We collected 205 papers published between 2006 and 2023 for the bibliometric analysis for the keyword co-occurrence and co-citation analysis, generating backward- and forward-looking perspectives on the scholarship in healthcare supply chain risk management (HSCRM).

This study finds a growing scholarly interest in HSCRM. Using bibliometric tools and mapping, this study presents the overall research trends in HSCRM literature and identifies seven research, namely, clusters, cost analysis, allocation, performance management, patient safety, quality, risk assessment and logistics and four research themes, namely, resilience, risk management strategy, healthcare supply chain disruption and data analytics, through the keyword co-occurrence and co-citation analyses. A future research agenda is provided based on these clusters for further investigation in this field.

This study conducted bibliometric analysis to identify clusters and associated themes for insights for further research. This approach helps advance the scholarship and proactively apply the implications in practice beyond the reactive strategy to risk management in healthcare supply chain management.

Manufacturing capability is a crucial component of every nation’s economy and pharmaceuticals are frequently a significant part of the manufacturing sector. Pharmaceutical supply chains are essential to health-care systems, contributing to living quality and shorter hospital stays. This study aims to examine the role of multiple integrations on business performance (BP) through supply chain flexibility (SCF) and supply chain agility (SCA).

Data was collected from 198 supply chain professionals in the pharmaceutical sector of the developing economy of Pakistan. The sample was collected based on a nonprobability purposive sampling approach. A five-point Likert-scale survey was used and analyzed with the PLS-SEM technique using SmartPLS 4.

This study found that process integration (PI) does not affect SCA, whereas relationship integration and measurement integration positively affect SCA. SCA positively impacts BP. In contrast, all integrations significantly influenced supply flexibility and BP except for PI. Finally, SCF significantly mediates the relationship between all integrations and BP.

This study examined the relationships of multiple integrations on BP, directly and indirectly, through SCF and agility. The theory of dynamic capabilities has been applied and extended to increase the comprehensiveness of the findings. A developing economy’s pharmaceutical industry supply chain was examined, producing empirical evidence of the results.

Due to the environmental concerns in our society, governments are moving towards green purchasing. However, public sector organizations have substantial internal problems. By using a theory of natural resource-based view, this study aimed to analyse the influence of leadership styles and innovation capabilities on green purchasing in the public sector organizations of a developing economy.

Data was collected from 199 purchasing professionals of public sector organizations, and hypotheses were tested through a quantitative method using partial least square-structural equation modelling with the help of SmartPLS version 4 to validate the measurement model.

This study identified that transformational leadership and delegation style of leadership have a significant and positive effect on innovation capability and green purchasing. Similarly, innovation capability mediates the relationship between leadership styles and green purchasing. However, transformational leadership found a more substantial effect on innovation capability and green purchasing than the delegation leadership style.

Results provide insight into the role of leadership styles in green purchasing and innovation capabilities in public sector organizations. Thus, addressing the important issues of how leadership styles and innovative capabilities (IC) can improve green culture, specifically green purchasing, to enhance ecological sustainability.

Results provide insight into the role of leadership styles in green purchasing and innovation capabilities in public sector organizations. Thus, it addresses how leadership styles and IC can improve green culture, specifically green purchasing, to enhance ecological sustainability.

According to extensive analysis, employee agility is influenced by teamwork, coordination and the organizational environment. However, less consideration has been given to the role of work stressors (challenge, hindrance) in influencing employee agility. To address this research gap, this study sheds light on how the use of enterprise social media (ESM) for social and work purposes influences employee agility through work stressors.

This research also explores how ESM visibility enhances the interaction between work stressors and employee agility by using primary data obtained from Chinese workers. A total of 377 entries were analyzed using AMOS 24.10 tools. All the hypotheses were tested using structural equation modeling (SEM).

The findings revealed that ESM use (social and work) negatively impacts challenge and hindrance work stressors. The results also reflect that challenge stressors have a significant impact on employee agility, whereas hindrance stressors are negatively related to it. Furthermore, the outcome also indicated that increased ESM visibility reinforces the connection between challenge stressors and employee agility. However, ESM visibility did not indicate a significant moderating impact on the link between hindrance stressors and employee agility.

This study describes how ESM usage effects agility of stressed employees. This research also explores how ESM visibility improves the interaction between work stressors and employee agility. The study results contribute to growing research on social media and employee agility and suggest several points of guidance for managers.

Predictive digital twin technology, which amalgamates digital twins (DT), the internet of Things (IoT) and artificial intelligence (AI) for data collection, simulation and predictive purposes, has demonstrated its effectiveness across a wide array of industries. Nonetheless, there is a conspicuous lack of comprehensive research in the built environment domain. This study endeavours to fill this void by exploring and analysing the capabilities of individual technologies to better understand and develop successful integration use cases.

This study uses a mixed literature review approach, which involves using bibliometric techniques as well as thematic and critical assessments of 137 relevant academic papers. Three separate lists were created using the Scopus database, covering AI and IoT, as well as DT, since AI and IoT are crucial in creating predictive DT. Clear criteria were applied to create the three lists, including limiting the results to only Q1 journals and English publications from 2019 to 2023, in order to include the most recent and highest quality publications. The collected data for the three technologies was analysed using the bibliometric package in R Studio.

Findings reveal asymmetric attention to various components of the predictive digital twin’s system. There is a relatively greater body of research on IoT and DT, representing 43 and 47%, respectively. In contrast, direct research on the use of AI for net-zero solutions constitutes only 10%. Similarly, the findings underscore the necessity of integrating these three technologies to develop predictive digital twin solutions for carbon emission prediction.

The results indicate that there is a clear need for more case studies investigating the use of large-scale IoT networks to collect carbon data from buildings and construction sites. Furthermore, the development of advanced and precise AI models is imperative for predicting the production of renewable energy sources and the demand for housing.

This paper makes a significant contribution to the field by providing a strong theoretical foundation. It also serves as a catalyst for future research within this domain. For practitioners and policymakers, this paper offers a reliable point of reference.

Muslim engagement with cryptocurrencies (CC) raises fundamental questions rooted in religious faith: How should Muslims integrate Islamic Accounting principles like zakat into this new and rapidly evolving financial paradigm? Thus, it is essential to understand CC holders’ perceptions thoroughly and whether they are willing to pay zakat using crypto assets. This research aims to explore factors influencing Muslim CC holders’ intention to pay zakat on CC, emphasizing financial risk, theory of planned behavior (TPB) constructs and Shariah compliance’s moderating role.

This attempt uses a quantitative approach through a cross-sectional research design, using purposive sampling to gather data from Muslim CC holders. An extended theory of planned behavior (ETPB) model is applied to comprehensively analyze the key factors influencing intentions to pay zakat on CC. SmartPLS software is used to generate meaningful findings.

The study finds that financial risk associated with CC exerted a negative influence on TPB constructs, attitude (ATT), social norms (SN) and perceived behavioral control regarding zakat on CC (PBC). However, ATT and PBC positively shaped holders’ intention to pay zakat on CC. Interestingly, Shariah compliance-moderated interactions of TPB constructs on payment intentions were statistically significant.

With the rise of CC, a profound transformation is underway in the financial landscape. As this evolution unfolds, it becomes increasingly essential for stakeholders to understand how zakat could fit into such a new and rapidly evolving paradigm. A pioneering effort was made in this study by exploring Muslim CC holders’ intentions to fulfill zakat obligations, bridging a significant gap in the literature.

Previous research has demonstrated that Digital Twins (DT) are extensively employed to improve sustainable construction methods. Nonetheless, their uptake in numerous nations is still constrained. This study seeks to identify and examine the digital twin’s implementation barriers in construction building projects to augment operational performance and sustainability.

An iterative two-stage approach was adopted to explore the phenomena under investigation. General DT Implementation Barriers were first identified from extant literature and subsequently explored using primary questionnaire survey data from Hong Kong building industry professionals.

Survey results illustrated that Lack of methodologies and tools, Difficulty in ensuring a high level of performance in real-time communication, Impossibility of directly measuring all data relevant to the DT, need to share the DT among multiple application systems involving multiple stakeholders and Uncertainties in the quality and reliability of data are the main barriers for adopting digital twins' technology. Moreover, Ginni’s mean difference measure of dispersion showed that the stationary digital twin’s barriers adoption is needed to share the DT among multiple application systems involving multiple stakeholders.

The study’s findings offer valuable guidance to the construction industry. They help stakeholders adopt digital twins' technology, which, in turn, improves cost efficiency and sustainability. This adoption reduces project expenses and enhances environmental responsibility, providing companies a competitive edge in the industry.

This research rigorously explores barriers to Digital Twin (DT) implementation in the Hong Kong construction industry, employing a systematic approach that includes a comprehensive literature review, Ranking Analysis (RII) and Ginni’s coefficient of mean difference (GM). With a tailored focus on Hong Kong, the study aims to identify, analyze and provide novel insights into DT implementation challenges. Emphasizing practical relevance, the research bridges the gap between academic understanding and real-world application, offering actionable solutions for industry professionals, policymakers and researchers. This multifaceted contribution enhances the feasibility and success of DT implementation in construction projects within the Architecture, Engineering and Construction (AEC) sector.

The purpose of this study is to investigate the reasons (for and against) affecting owners' attitudes and intentions to use digital marketing (DM) strategies in tourism and hospitality (T&H) small and medium enterprises (SMEs), by employing the behavioral reasoning theory (BRT).

A survey method was used to collect data from 306 T&H (SMEs) owners and analyze the data through partial least square structural equation modelling (PLS-SEM).

The study results indicate that reasons significantly affect owners' attitudes and intentions to use DM in T&H (SMEs). The “RF” was as follows: perceived ease of use (PEU), perceived usefulness (PU), and trust in DM professionals” and the “RA” technological anxiety, usage barriers (UB), and perceived complexity (PC) effect on owners’ attitudes and intentions to use DM. Also, it indicates that openness to change value significantly affects the “RF” insignificant with “RA” and attitude.

The findings of this study emphasize that if owners/managers, governments, and policymakers overcome the “RA” that discourages and raises the knowledge about the “RF” in the adoption of DM, then the usage intention of DM strategies can rise in T&H (SMEs).

This study is the first to investigate the reasons (for and against) the owner’s attitude and intention to use DM in T&H (SMEs) by utilizing behavioral reasoning theory (BRT), technology acceptance model (TAM), and innovation resistance theory (IRT).