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In this chapter, the authors critically examine the application of unmeasured latent method factors (ULMFs) in human resource and organizational behavior (HROB) research, focusing on addressing common method variance (CMV). The authors explore the development and usage of ULMF to mitigate CMV and highlight key debates concerning measurement error in the HROB literature. The authors also discuss the implications of biased effect sizes and how such bias can lead HR professionals to oversell interventions. The authors provide evidence supporting the effectiveness of ULMF when a specific assumption is held: a single latent method factor contributes to the data. However, the authors dispute this assumption, noting that CMV is likely multidimensional; that is, it is complex and difficult to fix with statistical methods alone. Importantly, the authors highlight the significance of maintaining a multidimensional view of CMV, challenging the simplification of a CMV as a single source. The authors close by offering recommendations for using ULMFs in practice as well as more research into more complex forms of CMV.

Most Asians are directly or indirectly dependent on agriculture, and most live in rural areas. Since Asia is primarily an agricultural economy, rural tourism and agrotourism are critical in enabling growth. Agrotourism is a term that refers to the fusion of tourism and agriculture. The freshwater turtles (Batagur sp.) are a group of six turtles that once roamed southern Asia's great rivers and estuaries from the Indian Subcontinent to the Indonesian islands. Therefore, this review is to investigate the current state of agrotourism in Batagur sp. conservation and assess the associated challenges and opportunities. This review paper recognized the impacts and benefits for the rural site as an agrotourism industry. Moreover, three initiatives in Batagur sp. conservation programs were also discussed. Agrotourism, with a focus on the conservation of Batagur sp., is a vital driver of economic growth in rural Asian regions. It diversifies rural communities' income sources, enhancing economic stability and resilience.

The “chiralisation” of Euclidean polygonal tessellations is a novel, recent method which has been used to design new auxetic metamaterials with complex topologies and improved geometric versatility over traditional chiral honeycombs. This paper aims to design and manufacture chiral honeycombs representative of four distinct classes of 2D Euclidean tessellations with hexagonal rotational symmetry using fused-deposition additive manufacturing and experimentally analysed the mechanical properties and failure modes of these metamaterials.

Finite Element simulations were also used to study the high-strain compressive performance of these systems under both periodic boundary conditions and realistic, finite conditions. Experimental uniaxial compressive loading tests were applied to additively manufactured prototypes and digital image correlation was used to measure the Poisson’s ratio and analyse the deformation behaviour of these systems.

The results obtained demonstrate that these systems have the ability to exhibit a wide range of Poisson’s ratios (positive, quasi-zero and negative values) and stiffnesses as well as unusual failure modes characterised by a sequential layer-by-layer collapse of specific, non-adjacent ligaments. These findings provide useful insights on the mechanical properties and deformation behaviours of this new class of metamaterials and indicate that these chiral honeycombs could potentially possess anomalous characteristics which are not commonly found in traditional chiral metamaterials based on regular monohedral tilings.

To the best of the authors’ knowledge, the authors have analysed for the first time the high strain behaviour and failure modes of chiral metamaterials based on Euclidean multi-polygonal tessellations.

This paper focuses on image-to-text manuscript processing through Handwritten Text Recognition (HTR), a Machine Learning (ML) approach enabled by Artificial Intelligence (AI). With HTR now achieving high levels of accuracy, we consider its potential impact on our near-future information environment and knowledge of the past.

In undertaking a more constructivist analysis, we identified gaps in the current literature through a Grounded Theory Method (GTM). This guided an iterative process of concept mapping through writing sprints in workshop settings. We identified, explored and confirmed themes through group discussion and a further interrogation of relevant literature, until reaching saturation.

Catalogued as part of our GTM, 120 published texts underpin this paper. We found that HTR facilitates accurate transcription and dataset cleaning, while facilitating access to a variety of historical material. HTR contributes to a virtuous cycle of dataset production and can inform the development of online cataloguing. However, current limitations include dependency on digitisation pipelines, potential archival history omission and entrenchment of bias. We also cite near-future HTR considerations. These include encouraging open access, integrating advanced AI processes and metadata extraction; legal and moral issues surrounding copyright and data ethics; crediting individuals’ transcription contributions and HTR’s environmental costs.

Our research produces a set of best practice recommendations for researchers, data providers and memory institutions, surrounding HTR use. This forms an initial, though not comprehensive, blueprint for directing future HTR research. In pursuing this, the narrative that HTR’s speed and efficiency will simply transform scholarship in archives is deconstructed.

As the tourism industry recovers from the devastating effects of the global pandemic, meeting the targets of the Sustainable Development Goals (SDGs) remains to be a global “deadline” where tourism is seen as a major contributor. While disruptions to business-as-usual practices such as COVID-19 present unprecedented challenges, they can also provide opportunities for strategic innovation to change behavior toward sustainable tourism experiences. Active transport for low-carbon tourism such as walking or cycling tours have risen in popularity in recent years, and especially postpandemic, as they provide opportunities for a more personalized experience while health and safety protocols can still be implemented. They also present health benefits for the individuals while contributing to environmental sustainability and climate mitigation strategies of the tourism industry. This book chapter presents cases of various forms of tourism activities that use active transport, focusing on walking tours and cycling tours. Various companies offering tours under these modes are discussed and presented. These two modes promote authentic cultural and heritage tourism experiences through the local experts that provide the services.

This study is the maiden attempt to understand the effect of specific human resource practices (HRPs) on employee retention (ER) with the mediation of job satisfaction (JS) and moderation of work experience (WE) and job hopping (JH) in the context of the textile industry.

This study adopted a quantitative methodology and applied quota sampling to gather data from employees (n = 365) of leading textile companies in India. The conceptual model and hypotheses were tested with the help of Partial Least Squares-Structural Equation Modelling (PLS-SEM).

The findings of a path analysis revealed that compensation and performance appraisal (CPA) have the highest impact on JS followed by employee work participation (EWP). On the other hand, EWP had the highest impact on ER followed by grievance handling (GRH). The study revealed that JS significantly mediates between HRPs like CPA and ER. During Multi-group analysis (MGA) it was found that the importance of EWP and health and safety (HAS) was more in employee groups with higher WE, but it was the opposite in the case of CPA. In the case of JH behavior, the study observed that EWP leads to JS in loyal employees. Similarly, JS led to ER, and the effect was more pronounced for loyal employees.

In the context of the Indian textile industry, this work is the first attempt to comprehend how HRPs affect ER. Secondly, it confirmed that JS is not a guaranteed mediator between HRPs and ER, it could act as an insignificant, partial or full mediator. Additionally, this study establishes the moderating effects of WE and JH in the model through multigroup analysis.

The objective of this study is to explore the structural attributes of the pharmaceutical industry before the onset of the COVID-19 pandemic by examining the relationship between inventory and firm performance and developing a taxonomy of pharmaceutical firms based on the earns-turns matrix.

This study examines the inventory–firm performance linkage, considering both total inventory and its discrete inventory components in pharmaceutical firms. In addition, this research develops a new taxonomy of pharmaceutical firms based on the earns-turns matrix. A large panel dataset of firms in the US pharmaceutical industry was collected for the period 2000–2019.

The results reveal that strategic groups identified based on this taxonomy show different levels of profitability and inventory turns in the earns-turns matrix. Most pharmaceutical firms moved from the low-right to the top-left section in the earns-turns matrix, indicating that these firms have generally pursued profitability rather than effective inventory management.

This study explores the structural attributes of the pharmaceutical industry using the earns-turns matrix. This two-dimensional analysis may not, however, capture the full complexity of inventory–firm performance dynamics.

The mapping of strategic groups on the earns-turns matrix provides a useful tool for visual representations of the dynamics of strategic groups in terms of financial performance and inventory management performance. Practitioners can use the earns-turns matrix to benchmark their firm's position against their competitors.

This study broadens the scope of operations management research by introducing the earns-turns matrix as an empirical validation tool for operational and strategic management theories. This study emphasizes the effectiveness of the earns-turns matrix in analyzing strategic groups of pharmaceutical firms.

The purpose of this study is to determine research areas that are most favorable in supporting the development and manufacturing of electric vehicle (EV) components locally in Indonesia for 2025–2035. Therefore, will provide direction for the formulation of the related government policies and programs. Consequently, an EV technology research priority must be identified.

A technology foresight (TF) procedure which consists of a STEEPV analysis, followed by scenarios development and expert elicitation techniques, was conducted to determine an EV technology research priority that may direct future specific local component innovations, and therefore businesses.

The results of this study indicate that research in a range of EV battery technologies, technologies relating to a variety of key components (to increase local content) and autonomous systems were important to support the local development and manufacturing of EV components in Indonesia.

In this study, the scenarios development process was conducted based on selected available experts, mostly internally from BRIN. Some biased opinions may be present.

There have not been any TF studies regarding the development of EV technology research priority in Indonesia.

The effects of integrated reporting quality (IRQ) have been debated in increasing empirical studies. Several IRQ measures, different theoretical approaches and multiple contexts have been adopted and investigated, leading to mixed results. By using the meta-analytic technique, this study aims to contribute to the accounting literature, reconciling the conflicting results on the effects of IRQ and providing objective conclusions to complement narrative literature reviews.

A sample of 45 empirical papers from 2013 to 2022, with 653 effect sizes, was used to assess the effects associated with IRQ. The papers were clustered into five groups (market reaction, financial performance, cost of capital, financial analysts’ properties and managerial decisions) based on the different consequences of IRQ investigated in the primary studies. A random-effects meta-regression model was used to explore all sources of heterogeneity together.

The meta-regression results confirm that IRQ positively influences firms’ market valuation and financial performance and hampers opportunistic managerial behaviour by improving corporate transparency, mitigating information asymmetry and encouraging accountability. Moreover, differences in the study characteristics affect the strength of the relationship object of interest.

Through meta-analysis, this study provides a broader overview of the effects of IRQ by enhancing the generalisability of the findings. The results also pave the way for additional evidence on the outcome variables affected by the quality of integrated disclosure.

Corporate leadership and environmental, social and governance (ESG) performance are closely intertwined, as effective corporate leadership can facilitate the achievement of strong ESG performance. Thus, the purpose of the study is to investigate the impact of corporate board leadership on the ESG performance of listed firms.

The sample has been taken from the listed firms of the Nifty 500 index spanning the period of 10 years from 2012 to 2022. Dynamic panel data estimations are applied through a fixed effect model.

The findings of this study revealed that board size, board independence and board qualification have a significant positive influence on ESG performance. It is evident that good corporate governance practices can positively influence ESG performance by fostering accountability, transparency and ethical behavior, as well as better integrating ESG considerations into their decision-making processes and ensuring that ESG issues are prioritized at the highest levels of management. Further findings also revealed that chief executive officer (CEO) duality has a significant negative relationship with ESG performance, which goes against the belief of stakeholder theory.

It has practical implications for policymakers, as they can enact new regulations pertaining to the CEO’s position in the organizations to make corporate governance responsible for improved sustainability and ESG performance.

There are very few studies analyzing the impact of corporate board structure on ESG performance related to emerging markets. Thus, this study contributes to that literature by using the methodology GMM panel data for the first time as per our knowledge