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This study aims to: (1) investigate the relationship/connection between organizational change (OC) and organizational resilience (OR) and (2) provide a basis for understanding how organizational change can underpin or build organizational resilience.

An extensive literature review has been made to discuss the goals of OC as well as the enablers of OR. A number of conceptual models have been introduced to demonstrate the correlation between OC and OR and the potential role of OC in supporting OR. Empirical findings were also introduced in order to support the theoretical basis of this research.

This study argues that OC can be practiced for the purpose of building or supporting OR. A variety of views have been introduced to demonstrate the correlation between OC and OR and the role of OC in supporting OR.

The purpose and scope of OC should not only be confined to enabling organizations to respond to the dynamics of their business environments but also to enable organizations to withstand a wider range of internal disruptions, major incidents and external factors. This perspective provides a broader insight that is different from the traditional conceptualization of the goals and purpose of OC.

To the author’s knowledge, this is one of very few studies that discuss the correlation between OC and OR and the role of OC in building OR. This explains the need for more practical change initiatives that aim to elevate levels of OR.

Increasing overhang of serviced apartments poses a serious concern to the national property market. This study aims to examine the impacts of macroeconomic determinants, namely, gross domestic product (GDP), consumer confidence index (CF), existing stocks (ES), incoming supply (IS) and completed project (CP) on serviced apartment price changes.

To achieve more accurate, quality price changes, a serviced apartment price index (SAPI) was constructed through a self-developed hedonic price index model. This study has collected 1,567 transaction data in Kuala Lumpur, covering 2009Q1–2018Q4 for price index construction and data were analysed using the vector autoregressive model, the vector error correction model and the fully modified ordinary least squares (OLS) (FMOLS).

Results of the regression model show that only GDP, ES and IS were significantly associated with SAPI, with an R² of 0.7, where both ES and IS have inverse relationships with SAPI. More precisely, it is predicted that the price of serviced apartments will be reduced by 0.56% and 0.21% for every 1% increase in ES and IS, respectively.

Therefore, government monitoring of serviced apartments’ future supply is crucial by enforcing land use-planning regulations via stricter development approval of serviced apartments to safeguard and achieve more stable property prices.

By adopting an innovative approach to estimating the response of price change to supply and demand in a situation where there is no price indicator for serviced apartments, the study addresses the knowledge gap, especially in terms of understanding what are the key determinants of, and to what extent they influence, the SAPI.

This study aims to investigate the negative interpersonal antecedents, emotional mediators and boundary conditions of knowledge sabotage behavior.

The authors collected data from 275 Chinese employees using convenience sampling and snowball sampling across three stages. Subsequently, the authors used both hierarchical regression and bootstrap methods to test the proposed hypotheses.

The results confirmed that workplace ostracism has positive effects on employee knowledge sabotage behavior both directly and via employee anger. In addition, the authors found that employee bottom-line mentality (BLM) moderates not only the direct effect of workplace ostracism on employee anger but also the indirect effect of employee anger in this context. Employee conscientiousness moderates only the direct effect of workplace ostracism on employee anger and does not moderate the indirect effect.

To the best of the authors’ knowledge, this study not only explores the influence of workplace ostracism on employee knowledge sabotage behavior for the first time but also elucidates the underlying emotional mechanisms (anger) and boundary conditions (employee BLM and conscientiousness) by which workplace ostracism influences employee knowledge sabotage behavior, thus deepening the understanding of how knowledge sabotage emerges in organizations.

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.

This study aims to examine the challenges for green retrofitting implementation in existing residential buildings to lower the running cost and achieve a better energy-efficient system.

This study adopted a qualitative approach by interviewing conveniently selected 16 construction professionals, made up of architects, quantity surveyors and engineers. Data received were analysed using the content analysis method.

The findings revealed that the main barriers to incorporating green retrofitting in the existing residential buildings as the nature of the existing structures, limited knowledge, not being a priority and high costs involved in the process. Moreover, other factors influencing property developers’ decision to apply energy-efficient principles in a residential home include cost (initial capital and maintenance), level of knowledge, nature of the climate in the area, local legislation, more independence and increasing the property’s market value and environmental aspect.

This study is limited to South Africa; thus, the literature available was limited.

People’s perceptions, either wrong or correct, affect their ability to make an informed decision to adopt green retrofitting principles, thereby denying them the opportunity to reap the associated benefits. Therefore, there is an urgent need for the construction industry stakeholders and government to increase educational opportunities for property owners on the importance of green retrofitting.

This study provides the occupants with the possible barriers and problem areas with implementing these principles. They will thus make an informed decision when implementing sustainable design methods.

There is growing recognition that effective project control systems (PCS) are critical to the success of projects. The relationship between the individual elements of PCS and successfully achieving project objectives has yet to be explored. This research investigates the enablers and barriers that influence the elements of PCS success and drive project objectives.

This study adopts a mixed approach of descriptive analysis and regression models to explore the impact of six PCS elements on project outcomes. Petroleum and chemical projects in Saudi Arabia were selected as a case study to validate the research model.

Data from a survey of 400 project managers in Saudi’s petroleum and chemical industry reveal that successful PCS are the key to achieving all project outcomes, but they are particularly critical for meeting project cost objectives. Project Governance was identified as the most important of the six PCS elements for meeting project objectives. A lack of standard processes emerged as the most significant barrier to achieving effective project governance, while having skilled and experienced project team members was the most significant enabler for implementing earned value.

The study offers a direction for implementing and developing PCS as a strategic tool and focuses on the PCS elements that can improve project outcomes.

This research contributes to project management knowledge and differs from previous attempts in two ways. Firstly, it investigates the elements of PCS that are critical to achieving project scope, schedule and cost objectives; secondly, enablers and barriers of PCS success are examined to see how they influence each element independently.

This paper aims to concentrate on recent innovations in flexible wearable sensor technology tailored for monitoring vital signals within the contexts of wearable sensors and systems developed specifically for monitoring health and fitness metrics.

In recent decades, wearable sensors for monitoring vital signals in sports and health have advanced greatly. Vital signals include electrocardiogram, electroencephalogram, electromyography, inertial data, body motions, cardiac rate and bodily fluids like blood and sweating, making them a good choice for sensing devices.

This report reviewed reputable journal articles on wearable sensors for vital signal monitoring, focusing on multimode and integrated multi-dimensional capabilities like structure, accuracy and nature of the devices, which may offer a more versatile and comprehensive solution.

The paper provides essential information on the present obstacles and challenges in this domain and provide a glimpse into the future directions of wearable sensors for the detection of these crucial signals. Importantly, it is evident that the integration of modern fabricating techniques, stretchable electronic devices, the Internet of Things and the application of artificial intelligence algorithms has significantly improved the capacity to efficiently monitor and leverage these signals for human health monitoring, including disease prediction.

The ecosystem concept has attracted attention in information system research to explain business competition, innovation and many other emerging phenomena. Existing studies focus more on a single ecosystem type or a single ecosystem goal and pay little attention to the ecosystem’s evolution. The objective of the study is to investigate the factors that impact the evolution of the information ecosystem (IE) to gain a better understanding of strategic thinking.

The IE involves many actors, so the multi-case study approach is conducted with purposeful sampling to recruit all the significant ecosystem actors. The collected qualitative data are analyzed by coding data, exploring data relationships and structuring pattern steps; institutional theory is used as a theoretical framework.

The results demonstrate that industry practices, laws and regulations, new actors and the mimetic pressure of outsourcers drive the growth of the ecosystem. Strategy intention, cost pressure and normative pressure all contribute to the IE’s evolution.

The concept of ecosystems has attracted attention in information system research. The study investigates the factors contributing to the evolution of the IE from an institutional theory perspective. Our suggestion is that new players can find a niche in offering information technology (IT)/ information services (IS)-related solutions to survive in the ecosystem; however, they need to pay attention to the normative pressure.

This study explores whether the unique organizational form of family firms helps to mitigate the negative effects caused by the announcement of product recalls.

The authors use an event study, for a sample of 2,576 product recalls in the United States (US) automobile industry, between January 2010 and June 2021.

The authors found that stock market's reaction to a product recall announcement is less negative for family firms. This superior performance is partially driven by the family firms' long-term investment horizons and higher strategic emphasis on product quality. However, the relationship between family ownership and cumulative abnormal returns around product recall announcements is nonlinear as the impact of family ownership starts by being positive but becomes negative for higher levels of family ownership. The authors also find that family firm's chief executive officer (CEO) and managerial ownership influence positively the stock market reaction to product recall announcements.

This work has several implications for family firms' management as well as for investors and financial analysts. First, as higher managerial ownership is associated with a greater emphasis on product quality, decreasing stock market losses when a product recall occurs, family firms should consider increasing equity-based compensation. Second, as there seems to exist an optimal proportion of family ownership, family firms should consider the risks of increasing too much their ownership share. Third, investors and financial analysts can use the results in the study to help them in their investment and trading decisions in the stock market.

The authors extend the knowledge of product recalls by studying the under-researched role of the flexible, internally focused culture of family businesses on the stock market reaction to product recalls.

Every day, small and big incidents happen all over the world, and given the human, financial and spiritual damage they cause, proper planning should be sought to deal with them so they can be appropriately managed in times of crisis. This study aims to examine humanitarian supply chain models.

A new model is developed to pursue the necessary relations in an optimal way that will minimize human, financial and moral losses. In this developed model, in order to optimize the problem and minimize the amount of human and financial losses, the following subjects have been applied: magnitude of the areas in which an accident may occur as obtained by multiple attribute decision-making methods, the distances between relief centers, the number of available rescuers, the number of rescuers required and the risk level of each patient which is determined using previous data and machine learning (ML) algorithms.

For this purpose, a case study in the east of Tehran has been conducted. According to the results obtained from the algorithms, problem modeling and case study, the accuracy of the proposed model is evaluated very well.

Obtaining each injured person's priority using ML techniques and each area's importance or risk level, besides developing a bi-objective mathematical model and using multiple attribute decision-making methods, make this study unique among very few studies that concern ML in the humanitarian supply chain. Moreover, the findings validate the results and the model's functionality very well.