Search results

Drawing on social network and information diffusion theories, the authors study the impact of the structural characteristics of a seller’s local social network on her promotion effectiveness in social commerce.

The authors define a local social network as one formed by a focal seller, her directly connected users and all links among these users. Using data from a large social commerce website in China, the authors build econometric models to investigate how the density, grouping and centralization of local social networks affect the number of likes received by products posted by sellers.

Local social networks with low density, grouping and centralization are associated with more likes on sellers’ posted products. The negative effects of grouping and centralization are reduced when density is high.

The paper deepens the understanding of the determinants of social commerce success from a network structure perspective. In particular, it draws attention to the role of sellers’ local social networks, forming a foundation for future research on social commerce.

This study investigates the repetitive mixed sampling (MRS) plan based on the Cpk index that was proposed by Aslam et al. (2013a). They were the first to study the MRS plan, but they did not pay attention to the fact that submitting to the variable inspection a sample that was first submitted to the attribute inspection, truncates the X observations. In addition, they did not work with an accurate expression to calculate the probabilities of the Cpk statistic.

The authors presented the results based on their original sampling plan through Monte Carlo simulation and defined the theoretical results of their plan when the sample submitted to the variable inspection is no longer the same one submitted to the attribute inspection.

The β risks of the optimum sampling plans presented by Aslam et al. (2013a) are pretty high, exceeding 46%, on average – this same problem was also observed in Saminathan and Mahalingam (2018), Balamurali (2020) and Balamurali et al. (2020), where the β risks of their proposed sampling plans are yet higher.

In terms of originality, the authors can declare the following. It is not a big deal to propose new sampling plans, if one does not know how to obtain their properties. The miscalculations of the sampling plans risks are dangerous; imagine the situation where the acceptance of bad lots exceeds 50% just because the sampling plan was incorrectly designed. Yes, it is a big deal to warn that this type of problem is arising in a growing number of papers. The authors of this study are the pioneers to discover that many studies focusing on the sampling plans need to be urgently revised.

The proliferation of bibliometric review articles is a true reflection of how bibliometrics is gaining popularity and has been widely adopted in various disciplines. The growing interest of scholars has encouraged us to dwell upon the what, why, when, how, and where of bibliometric literature reviews. The study explained the bibliometric review with the standpoint that it can be considered a strong review method for analyzing a large volume of data and scholars can supplement their traditional reviews with bibliometric reviews to strengthen their knowledge. This will help researchers to justify the (a) need for a study on the particular topic; (b) type or method of review chosen; (c) number of articles selected; (d) inclusion and exclusion criterion; (e) method of analysis; and (f) presentation of the findings.

In this paper, the authors examine the short-term and long-term impact of general economic policy uncertainty (EPU) and crypto-specific policy uncertainty on Bitcoin’s (BTC) exchange inflows – a form of crypto investor behaviors that the authors expect to drive the cryptocurrency volatility.

The authors use an autoregressive distributed lag (ARDL), coupled with the bounds testing approach by Pesaran et al. (2001), to analyze a weekly dataset of BTC’s exchange inflows and relevant policy uncertainty indices.

The authors observe both short-term and long-term impacts of the crypto-specific policy uncertainty on BTC’s exchange inflows, whereas the general EPU only explains these inflows in a short-term manner. In addition, the authors find exchange inflows of BTC “Granger” cause its price volatility. Furthermore, the authors document a significant and relatively persistent response of BTC volatility to shocks to its exchange inflows.

This study’s findings offer significant contributions to research in policy uncertainty and investor behaviors.

This study provides empirical evidence for the first time on how different measures of monetary policy affect banking profitability in Ghana.

Providing empirical evidence on how different measures of monetary policy affect banking profitability in Ghana using 29 banks for period between 2006 and 2016, new monetary indexes are developed and a robust panel random effect models is employed with year effect controls.

The results show that while increase in monetary policy basis point reduced banking profitability, average monetary policy rate stimulated banking profitability. Interestingly, the monetary policy basis point and rate indexes developed reduced and enhanced banking profitability, respectively. While these results may sound contradictory, they have both theoretical and empirical backing. Thus, basis point increments serve a monetary policy tightening condition which leads to higher loan prices, lower borrowing and declined profitability in the short run. However, in the long run, banks adjusted their loan prices and deposits to reflect basis point changes in their favor, hence the positive effect of average monetary policy rate on banking profitability. Additionally, monetary policy easing which represents decline in monetary policy basis point and rate enhances banking profitability.

These findings imply bank managers may take advantage of monetary policy easing to maximize profits in the banking sector of Ghana. Also, the monetary policy committee must be mindful of monetary policy tightening through basis point change since upward basis point increments reduce banking profitability.

This study provides empirical evidence for the first time on how different measures of monetary policy (developing indexes from monetary policy basis point and monetary policy rate) affect banking profitability in an emerging economy as Ghana.

This study aims to explore the mechanism of the relationships between financial and non-financial outcomes and gender equality through a case study of a Japanese bank that has consistently pursued gender equality.

A single case study was adopted to explore the outcomes of promoting gender equality. Primary data were collected from 12 semi-structured interviews. Data were analysed by rereading and coding the interview responses coded to generate themes.

Through governance reform in Company A, women have been placed in top management positions and the number of female managers has increased, allowing frontline intentions to be reflected in decision-making. The increased number of female managers has led to a decrease in female turnover, men taking parental leave, improved training of female managers and the recruitment of excellent new graduates. The appropriate allocation of jobs to female managers and employees also meets customer needs and has led to increased sales. Finally, involvement of female employees in product development in male-dominated workplaces brings women’s experiences and perspectives to product development, resulting in the development of products that are favoured by customers.

This study determined the mechanism behind the relationships between financial and non-financial outcomes and gender equality, based on agency, upper echelons, resource dependence, institutional and social role theories. It also contributes to gender equality research methodology by providing compelling qualitative stories of gender equality outcomes to increase a company’s commitment to promoting gender equality.

This study aims to analyze the factors affecting tea-producing farmers' intention to use e-commerce exchanges (ECEs) to sell their products, combining the technology acceptance model (TAM) theory and barrier factors.

The authors use the generalized structural equation modeling (GSEM) to analyze the intermediate model that is built on TAM.

Research results show that perceived usefulness (PU) and perceived ease of use (PEU) significantly influence farmers' intention to use ECEs to sell their products. However, knowledge and information barriers hinder farmers' intention to use such ECEs.

Encouraging farmers to use ECEs is the most helpful solution for agricultural economic development in the context of the Covid-19 pandemic.

From an academic perspective, this is the first study that combines the TAM theory of Davis (1989) and barrier factors to analyze farmers' intention to use ECEs. The findings are valuable references for policymakers to propose strategies for agricultural economic development during the current pandemic. At the same time, the empirical results obtained from this study provide good orientations for agricultural economic development 4.0 in the future.

This cross-sectional online survey in Oman in April 2021 aimed to assess university students' resilience, stress levels and meaning during the COVID-19 pandemic and identify characteristic profiles.

A cross-sectional survey design was used to collect data from full-time students at one University in Oman. Outcomes included sociodemographic information, the brief resilience scale, the perceived stress scale-4 and the meaning in life questionnaire to explore the students' profiles.

A total of 964 students participated (response rate = 34.8%), of which 35% had low resilience scores. The average perceived stress, presence of meaning in life and search for meaning in life scores were 7.9 ± 2.3, 24.2 ± 6.9 and 24.9 ± 7.7, respectively. Cluster analysis identified three groups: low-risk and fewer impacts (cluster A, n = 503, 523%), moderate-risk and moderate impacts (cluster B, n = 160, 16.6%) and high-risk and more impacts (cluster C, n = 301, 31.2%). Cluster C students experienced more psychological problems and were at high risk during the pandemic.

The respondents' honesty is a possible error that could influence the results. Low response rates limit its generalizability, and cause-effect relationships among mental health outcomes cannot be discerned.

This study identified three distinct groups of students, each with different levels of severity in their health problems. There is an increased need for education and counseling to support students during this period, and university management should focus on implementing personal precautionary measures and providing high-tech, user-friendly platforms for students to enhance their learning.

These findings suggest that tailored strategies should be developed to address the unique psychological needs of each group. The study provides important information for university management to understand the pandemic's psychological impact on students and develop effective interventions to support their well-being.

Several studies have examined the impact of market fundamentals on house prices. However, the effect of economic sectors on housing prices is limited despite the existence of two-speed economies in some countries, such as South Africa. Therefore, this study aims to examine the impact of mining activities on house prices. This intends to understand the direction of house price spreads and their duration so policymakers can provide remediation to the housing market disturbance swiftly.

This study investigated the effect of mining activities on house prices in South Africa, using quarterly data from 2000Q1 to 2019Q1 and deploying an auto-regressive distributed lag model.

In the short run, we found that changes in mining activities, as measured by the contribution of this sector to gross domestic product, impact the housing price of mining towns directly after the first quarter and after the second quarter in the non-mining cities. Second, we found that inflationary pressure is instantaneous and impacts house prices in mining towns only in the short run but not in the long run, while increasing housing supply will help cushion house prices in both submarkets. This study extended the analysis by examining a possible spillover in house prices between mining and non-mining towns. This study found evidence of spillover in housing prices from mining towns to non-mining towns without any reciprocity. In the long run, a mortgage lending rate and housing supply are significant, while all the explanatory variables in the non-mining towns are insignificant.

These results reveal that enhanced mining activities will increase housing prices in mining towns after the first quarter, which is expected to spill over to non-mining towns in the next quarter. These findings will inform housing policymakers about stabilising the housing market in mining and non-mining towns. To the best of the authors’ knowledge, this study is the first to measure the contribution of mining to house price spillover.

Institutional, economic, social and technological advancements enable openness to cope with wicked public management issues. Although open innovation (OI) is becoming a new normality for public sector entities, scholarly knowledge on this topic is not fully systematized. The article fills this gap, providing a thick and integrative account of OI to inspire public management decisions.

Following the SPAR-4-SLR protocol, a domain-based literature review has been accomplished. Consistently with the study purpose, a hybrid methodology has been designed. Bibliographic coupling permitted us to discover the research streams populating the scientific debate. The core arguments addressed within and across the streams were reported through an interpretive approach.

Starting from an intellectual core of 94 contributions, 5 research streams were spotted. OI in the public sector unfolds through an evolutionary path. Public sector entities conventionally acted as “senior partners” of privately-owned companies, providing funding (yellow cluster) and data (purple cluster) to nurture OI. An advanced perspective envisages OI as a public management model purposefully enacted by public sector entities to co-create value with relevant stakeholders (red cluster). Fitting architectures (green cluster) and mechanisms (blue cluster) should be arranged to release the potential of OI in the public sector.

The role of public sector entities in enacting OI should be revised embracing a value co-creation perspective. Tailored organizational interventions and management decisions are required to make OI a reliable and dependable public value generation model.

The article originally systematizes the scholarly knowledge about OI, presenting it as a new normality for public value generation.