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This article investigates the long-run impact of remittance inflows on agricultural productivity (AGP) in emerging Asian economies (Bangladesh, Sri Lanka, Malaysia, India, Nepal, Philippines, Pakistan, and Vietnam), employing a panel dataset from 2000 to 2018.

This study initially applies cross-sectional dependence (CSD), second-generation unit root, Pedroni, and Westerlund panel co-integration techniques. Next, it uses the augmented mean group (AMG) and common correlated effect mean group (CCEMG) methods to investigate the long-term impact of remittance inflows on AGP while controlling for several other important determinants of agricultural growth, such as cultivated area, fertilizers, temperature change, credit, and labor force.

The empirical findings are as follows: The results first revealed the existence of CSD and long-term co-integration between AGP and its determinants. Second, remittance inflows significantly boosted AGP, indicating that remittance inflows played a crucial role in improving AGP. Third, global warming (changes in temperature) negatively impacts AGP. Finally, additional critical elements, for instance, cultivated area, fertilizers, credit, and labor force, positively affect AGP.

This study suggests that policymakers of emerging Asian economies should develop an exclusive remittance-receiving system and introduce remittance investment products to utilize foreign funds and mitigate agricultural production risks effectively.

This is the first empirical examination of the long-term impact of remittance flows on agricultural output in emerging Asian economies. This study utilized robust estimation methods for panel data sets, such as the Pedroni, Westerlund, AMG, and CCEMG tests.

The authors examine the impact of asymmetric information on firm's financing decisions, the feedback effect of changes in capital structure on the level of asymmetric information, and the speed of adjustments in capital structure on its target leverage.

The authors extract the data on 280 non-financial firms listed in the Pakistan Stock Exchange (PSX) from the DataStream. The authors implement the generalized method of moments (GMM), complemented by the fixed effect model (FEM) to estimate the model coefficients.

The authors find that asymmetric information significantly affects the financing decisions; and that on average, firms adjust 26% of the total debt toward their target capital structure. The negative effect from the difference between the observed and target changes in leverage on asymmetric information confirms that capital structure changes act as a signal for future profitability and helps the management to lower its level of asymmetric information.

The findings offer fresh insight into the effect of asymmetric information on financing decisions, as well as the speed of adjustment of capital structure toward its target leverage, in the context of the firms working in emerging markets like Pakistan. To the authors’ best knowledge, this is the first study to investigate the impact of asymmetric information on financing decisions that incorporate firm's age, size and the global financial crises 2007–2008. The authors construct an asymmetric information index using both accounting and finance measures of asymmetry.

The multidimensional complexity of urban settlements is increasing and the problem of spaces and territories brought to the scale of smart cities is a critical global issue. This study aims to analyse the scientific production in the Web of Science (WoS) on the relationship between smart cities and the eight urban dimensions defined by the World Economic Forum (WEF) in the period 1990 to 2021, in order to establish which countries lead the knowledge related to the search for sustainable living conditions for people and how this knowledge contributes to improving stakeholders' decision-making.

The methodological steps followed in the study were: (1) Identification and selection of keywords. (2) Design and application of an algorithm to identify these selected keywords in titles, abstracts and keywords using WoS terms to contrast them. (3) Data processing was performed from Journal Citation Report (JCR) journals during the year 2022.

This study identified the authors, institutions and countries that publish the most globally on the topic of Smart Cities. The acceleration in the integration of new technologies and their impact on population conglomerates and their relationship with urban dimensions were also analysed. The evidence found indicates that the USA and China are leading in this field.

This bibliometric study was designed to analyse a knowledge space not addressed in the scientific literature referred to the relationship between the concept of smart cities and the urban dimensions established by the WEF, the identification of new technologies that are converging to promote developments of new ways of managing urban dimensions and propose new knowledge spaces.

As a result, the current study attempted to investigate the impact of green human resource (GHR) practices on long-term performance, and the path has been explained through organizational identification, which is supported by social identity theory.

To achieve the present study's primary goal, data were obtained from manufacturing businesses and analyzed using partial least square (Smart PLS) on the data of 284 Pakistani small and medium-sized enterprises (SMEs) registered with the small and medium-sized enterprises development authority (SMEDA).

As a result, the findings show that organizational identification explains the indirect relationship between sustainable performance and green human resource management (GHRM).

To limit the limited negative effect on the environment and society, the findings provide several suggestions for the government authorities and policymakers to adopt green practices and policies.

Green practices are essential for a company to limit its negative environmental effect. Environmental critical problems among shareholders put pressure on the firm to implement GHR practices and organizational identification with long-term success.

The objective of this research is to evaluate and rank the factors influencing omnichannel (OC) logistics, while also investigating the significant impact of big data analytics in improving these drivers of OC logistics.

Using exploratory sequential mixed method design, an in-person interview survey was conducted to identify and stratifies the enablers of OC retailing. These interviews were supplemented with a case study in an apparel firm to prioritise the enablers of OC logistics. Further, a survey was conducted to understand the role of big data analytics in improving drivers of OC logistics as well as the role of Individual capability and organisational capability in big data usage for omnichannel retailing.

Findings represent that information management is the most important driver followed by inventory management and network design for improving OC logistics. Further, significant relationship between big data analytics and drivers of omnichannel logistics has been reported.

This study identifies and classifies the drivers of OC retailing relating to their level of criticality in OC logistics which will assists practitioners to prioritise their tasks for the successful development of OC logistics. The study will also help practitioners to use BDA for developing the drivers of OC.

The study substantiates and adds to the BDA literature by emphasising the positive role of BDA in development of OC driver and highlighting the significant role of drivers of BDA in its usage.

Insufficient productivity development in the global and Finnish infrastructure sectors indicates that there are challenges in genuinely achieving the goals of resource efficiency and digitalization. This study adapts the approach of capability maturity model integration (CMMI) for examining the capabilities for productivity development that reveal the enablers of improving productivity in the infrastructure sector.

Civil engineering in Finland was selected as the study area, and a qualitative research approach was adopted. A novel maturity model was constructed deductively through a three-step analytical process. Previous research literature was adapted to form a framework with maturity levels and key process areas (KPAs). KPA attributes and their maturity criteria were formed through a thematic analysis of interview data from 12 semi-structured group interviews. Finally, validation and refinement of the model were performed with an expert panel.

This paper provides a novel maturity model for examining and enhancing the infrastructure sector’s maturity in productivity development. The model brings into discussion the current business logics, relevance of lifecycle-thinking, binding targets and outcomes of limited activities in the surrounding infrastructure system.

This paper provides a new approach for pursuing productivity development in the infrastructure sector by constructing a maturity model that adapts the concepts of CMMI and change management. The model and findings benefit all actors in the sector and provide an understanding of the required elements and means to achieve a more sustainable built environment and effective operations.

The aim of this paper states that total productive maintenance (TPM) is an improvement tool which employs the effective utilization of employees in order to enhance the reliability of the equipment in consideration.

This paper identifies and evaluates the factors accountable for the adoption of TPM methodology in manufacturing organizations. Twenty-four factors affecting the TPM implementation are explored and categorized into five significant categories. Afterwards, these identified TPM factors have been evaluated by using a most popular Multi-criteria decision-making (MCDM) approach namely fuzzy pivot pairwise relative criteria importance assessment (F-PIPRECIA).

In this paper, through application of F-PIPRECIA, “Behavioural factor” is ranked first while “Financial factor” the last. Considering the sub-factors, “Top management support and commitment” is ranked first while “Effective use of performance indices” is ranked the last. A further sensitivity analysis indicates the factors that need higher level of attention.

The result of current research work may be exploited by the top administration of manufacturing enterprises for assessing their TPM adoption status and to recognize the frail links of TPM application and improve accordingly. Moreover, significant factors of TPM can be identified and deploy them successfully in their implementation procedure.

The conclusion obtained from this research enables the management to clearly understand the significance of each considered factor on the adoption of TPM in the organization and hence, provides effective utilization of resources.

This study aims to identify blockchain-related innovation trends that can improve trust networks in a smart city's transport and supply chain networks. Trust networks are crucial in building and maintaining the trust of citizens in smart cities. By promoting transparency and accountability, facilitating collaboration and innovation, enhancing citizen participation and protecting privacy and security, trust networks can help to ensure that smart cities are developed and implemented in a responsible and sustainable way. A systematic literature review identifies 60 conceptual and empirical studies. This research focuses on the current problems and developing procurement and supply chain strategy and the potential benefits of using blockchain in these areas. It suggests ways for the smart city's transport and supply chain networks to utilise blockchain to improve operations and supply chain strategy and identifies innovation trends related to blockchain. The study also includes a systematic literature review and Blockchain Transformation and Influence model as the basis to enhance trust networks in the supply chain.

Constructed upon knowledge-based view theory, this study investigates the influence of internal marketing (IM) on knowledge management (KM) processes in higher educational institutes (HEIs) in China and Pakistan. The study investigates the direct link between KM processes and organizational performance and indirect links via knowledge workers' productivity (KWP).

Data were collected from HEIs in China and Pakistan, and 784 survey responses were reported from academic and administrative staff (HEIs).

The result revealed that IM has a significant impact on KM processes, and KM processes impact organizational performance via the partial mediating effect of KWP in China, Pakistan and the overall sample. The multi-group analysis confirmed the substantial differential effect of KM processes on KWP in culturally different HEIs.

A lack of research establishes the inter-relationship between KM enabler (IM), KM processes, KWP and organizational performance in culturally diverse environments. This is one of the initial studies that examine the relationship between IM, KM processes, KWP and organizational performance in HEIs. Furthermore, this study contributes to the existing body of knowledge by conducting an in-depth empirical examination of IM, KM processes, KWP and OP in culturally diverse environments (i.e. China and Pakistan).

1. This research examines the influence of internal marketing (IM) on knowledge management (KM) processes by using knowledge workers' productivity (KWP) as a mediator between knowledge management (KM) and organizational performance.

2. Through the partly mediating effect of KWP, it was discovered that IM considerably influenced knowledge management processes and organizational performance in China, Pakistan and throughout the sample.

3. The multi-group analysis indicates that KMPs have a statistically significant influence on KWP.

This research examines the influence of internal marketing (IM) on knowledge management (KM) processes by using knowledge workers' productivity (KWP) as a mediator between knowledge management (KM) and organizational performance.

Through the partly mediating effect of KWP, it was discovered that IM considerably influenced knowledge management processes and organizational performance in China, Pakistan and throughout the sample.

The multi-group analysis indicates that KMPs have a statistically significant influence on KWP.

The study explores the impact of knowledge management (KM) enablers, i.e. trust and organizational climate, on KM processes. The study further observes the indirect relationship of KM processes on organizational performance via the mediating role of knowledge workers' satisfaction in cross-cultural settings.

This research used a survey of 784 educational and administrative personnel from higher education institutions (HEIs) in Pakistan and China. Smart Partial Least Square (PLS) 3.2.9 was employed to perform the analysis.

The result shows that trust and organizational climate influences KM processes, and these KM processes, in turn, impact organizational performance via the partial mediating effect of knowledge worker satisfaction (KWS) in Pakistan. The multi-group analysis confirmed the substantial differential effect of KM processes on KWS in culturally different HEIs. At the same time, the study's overall sample substantiated full mediation in China. Furthermore, the impact of KM processes on organizational performance did not substantiate in China.

Outcomes of this research affirm KM university practice and recommend how higher education academics and administrators prioritize trust, organizational climate, KM processes, and KWS while strengthening organizational performance in a culturally different environment.

A lack of research ascertains the inter-relationship between trust, organizational climate, KM processes, KWS, and organizational performance in culturally different environments. This is one of the initial studies that examine the relationship between trust, organizational climate, KM processes, KWS, and organizational performance in HEIs. The study empirically examines the inter-relationships among these variables and enlightens insights into the current literature by immediately investigating the mediating role of KWS in culturally different environments.