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It has been argued in the literature that structural changes in the financial markets, such as integration, have the potential to cause herding behavior or correlated behavioral patterns in traders. The purpose of this study is to investigate whether there is any financial herding behavior in the Latin American Integrated Market (MILA), a transnational stock market composed of Chile, Peru, Colombia and Mexico stock exchanges and whether there is any ARCH or GARCH effect in the herding behavior models.

This study uses the modified return dispersion approach on daily index return data. The sample period is from January 03, 2002 to May 07, 2019. The data are obtained from the MILA database. To count time-varying volatilities in herding models, the authors run ARCH family regression with GARCH (1,1) settings. Hwang and Salmon (2004) model is used as a robustness test.

The authors found strong herding behavior under the general market conditions and moderate and partial herding behavior under some specified markets circumstances, such as bull and bear markets and high-low volatility states. Moreover, the pre-MILA period exhibits more herding behavior than the post-MILA period. The empirical results show that most of the ARCH and GARCH effects are statistically significant, implying that the past information of stock returns and market volatility significantly affect the volatility of following periods, which can also explain the formation of herding tendency among investors. Finally, the results of the robustness tests (Hwang and Salmon, 2004) confirm herding in all periods, except full sample period for Mexico and post-MILA period for Mexico and Colombia.

This study investigates the herding behavior in the MILA market in terms of market return, volatility and timing. A limitation of the paper is that the authors have not included other factors on the formation of herding behavior, such as macroeconomic factors, effects of regional or international markets and policy influences. The authors will explore the issue in the extension of the paper.

As MILA is the first virtual integration of stock exchanges without merging, the study provides useful findings and draws good inferences of herding behavior in the MILA market in terms of market return, volatility and timing which are useful for academics, investors and policymakers in their investment and decision makings.

The paper provides useful findings and draws good inferences of herding behavior in the MILA market in terms of market return, volatility and timing which are not only useful in practical implications, but also in social implications.

This study contributes to the herding literature by examining four different hypotheses in respect of the unique case of transnational stock exchange without fusions or corporate mergers, where each market maintains its independence and regulatory autonomy. The authors also contribute to the literature by including both ARCH and GARCH effects in the herding behavioral models along the Hwang and Salmon (2004) approach.

In the 21st century, libraries are experiencing a significant decline in users due to shifting reading habits and the impact of technology, necessitating library transformation and a heightened emphasis on library marketing. Special libraries, in particular, rely heavily on patrons for survival, often due to their private ownership and limited resources. This paper aims to discuss the aforementioned objectives.

This paper examines the Taste Library, a special library in Hong Kong, and analyzes its current practices based on an interview with its founder, website content, and social media presence. The 7Ps Marketing Mix model is employed to assess the strengths and weaknesses of the library's current market position.

The Taste Library's existing practices exhibit limitations in attracting young patrons. To address this issue, we propose marketing strategies focused on enhancing social network presence, offering digitized content, and engaging in school outreach.

By concentrating on youth marketing, this study offers valuable insights for special libraries in developing strategic plans for transitioning and maintaining sustainability.

Few studies concentrate on marketing small special libraries, particularly in the East, within today's digitized economy.

In today's risk society, foundations are essential for sustaining democracies. However, the proof of a value-creating function of foundations is rarely assessed. Therefore, this study uses sensemaking theory and the communication value framework to explore to what extent a foundation achieved its overall mission in tackling societal challenges as opportunities.

This study employs a case study approach of a Swiss foundation. Through 20 semi-structured interviews with key stakeholders, insights about the value-creating function of the foundation were gained, showing how strategic communication activities contributed to the foundation's overall mission in various spheres of action.

The stakeholders overall identified a value-creating function of the foundation. The feedback obtained from the interviews could be structured along the lines of the communication value framework, with minor adjustments, showing that the foundation brought about value through its strategic communication regarding tangible assets (e.g. publicity), intangible assets (e.g. unique reputation), room for maneuver (e.g. renowned network) and opportunities for development (e.g. new formats). However, on each level, value-limiting factors have also been identified (e.g. limited publicity).

This study is the first to employ sensemaking theory to assess a foundation's value-creating function in achieving its overall mission by interviewing direct stakeholders. It is also one of the few studies in the field that analyzes strategic communication of foundations. Thus, this study adds methodological, theoretical and practical knowledge to foundation communication, value-creation and strategic communication management.

Drawing on the challenge–hindrance stressor framework and the “too-much-of-a-good-thing” principle, this study examined the curvilinear effects of two emic social challenge stressors (guanxi beliefs and participative decision-making (PDM)) and the moderating effect of an etic social hindrance stressor (perceived organizational politics) on Hong Kong and United States nurses’ job satisfaction.

A quantitative survey method was implemented, with the data provided by 355 Hong Kong nurses and 116 United States nurses. Structural equation modeling was used to examine the degree of measurement equivalence across Hong Kong and US nurses. The proposed model and the research questions were tested using nonlinear structural equation modeling analyses.

The results show that while guanxi beliefs only showed an inverted U-shaped relation on Hong Kong nurses’ job satisfaction, PDM had an inverted U-shaped relation with both Hong Kong and United States nurses’ job satisfaction. The authors also found that Hong Kong nurses experienced the highest job satisfaction when their guanxi beliefs and perceived organization politics were both high.

The results add to the comprehension of the nuances of the often-held assumption of linearity in organizational sciences and support the speculation of social stressors-outcomes linkages.

Managers need to recognize that while the nurturing and development of effective relationships with employees via social interaction are important, managers also need to be aware that too much guanxi and PDM may lead employees to feel overwhelmed with expectations of reciprocity and reconciliation to such an extent that they suffer adverse outcomes and become dissatisfied with their jobs.

First, the authors found that influences of guanxi beliefs and PDM are not purely linear and that previous research may have neglected the curvilinear nature of their influences on job satisfaction. Second, the authors echo researchers’ call to consider an organization’s political context to fully understand employees’ attitudes and reactions toward social interactions at work. Third, the authors examine boundary conditions of curvilinear relationships to understand the delicate dynamics.

This paper aims to clarify the impact of information asymmetry on users' payment rates and examine the role of perceived uncertainty (PU) and acceptable price (AP) in the relationship between information asymmetry and users' payment rates.

To test the influences of information asymmetry on users' payment rates, this paper collects 18,489 transaction data from the Chinese knowledge payment platform Zhihu with a Python crawler. This paper constructs a mediation model to define the relationship between information asymmetry and users' payment rates by introducing PU and AP as the mediators.

Information asymmetry negatively affects users' payment rates. In addition, PU and AP mediate the information asymmetry in users' payment rates bond.

This study only explores the mediators of the information asymmetry users’ payment rates bond, ignoring the effect of potential moderators, which would be an important direction for future research.

The findings of this paper suggest that information communication is essential in knowledge market transactions. Knowledge providers, as well as knowledge platforms, should enhance information exchange with consumers in order to increase product sales.

This paper provides a new perspective for understanding how information asymmetry affects users' payment rates and helps to guide suppliers to improve product quality. The research framework of this paper is universal to a certain extent.

This paper is one of the first to propose using PU and AP to construct a mediation model to study the information asymmetry between users' payment rates relationship. It provides a new perspective for understanding the channel of information asymmetry in customer behavior.

Considering the existing evidence on the impact of female board members on the default risks of an organization, the purpose of this study is to investigate the effect of board gender diversity, alongside institutional characteristics and macroeconomic factors, on the financing costs of microfinance institutions (MFIs).

This study collected unbalanced panel data of 1,190 unique MFIs between 2010 and 2018 from the World Bank. The collected data, which covers a total of 95 developing and emerging countries, was thereafter analyzed using the pooled ordinary least squares and random effects model. To overcome endogeneity and omitted variable bias (e.g. time-invariant variables), the authors have also used the generalized method of moments and fixed effects model, respectively. Different proxies of board gender diversity and sub-sample analysis by regions were further undertaken to examine the robustness of the obtained results.

The findings of this study revealed that board gender diversity has a statistically significant negative effect on the financing costs of MFIs. This suggests that a gender-diverse board can generate cheaper funding for MFIs by minimizing their default risks through effective monitoring and strategic management. Furthermore, the negative impact of board gender diversity on financing costs appears to be more pronounced when there is a minimum of two female board members in the boardroom of MFIs. The results of this study remain consistent and valid regardless of alternate model specifications (e.g. sub-sample analysis, use of alternative proxies of board gender diversity and application of different estimators) and endogeneity issues. Ultimately, the findings in this study reiterate the importance of promoting and implementing gender diversity in the boardroom to minimize the financing costs of MFIs.

This study investigated the relationship between board gender diversity and financing costs of MFIs by using relatively recent and global data. The minimum number of female board members required to significantly reduce the financing costs of MFIs was also identified.

Path planning is an important part of UAV mission planning. The main purpose of this paper is to overcome the shortcomings of the standard particle swarm optimization (PSO) such as easy to fall into the local optimum, so that the improved PSO applied to the UAV path planning can enable the UAV to plan a better quality path.

Firstly, the adaptation function is formulated by comprehensively considering the performance constraints of the flight target as well as the UAV itself. Secondly, the standard PSO is improved, and the improved particle swarm optimization with multi-strategy fusion (MFIPSO) is proposed. The method introduces class sigmoid inertia weight, adaptively adjusts the learning factors and at the same time incorporates K-means clustering ideas and introduces the Cauchy perturbation factor. Finally, MFIPSO is applied to UAV path planning.

Simulation experiments are conducted in simple and complex scenarios, respectively, and the quality of the path is measured by the fitness value and straight line rate, and the experimental results show that MFIPSO enables the UAV to plan a path with better quality.

Aiming at the standard PSO is prone to problems such as premature convergence, MFIPSO is proposed, which introduces class sigmoid inertia weight and adaptively adjusts the learning factor, balancing the global search ability and local convergence ability of the algorithm. The idea of K-means clustering algorithm is also incorporated to reduce the complexity of the algorithm while maintaining the diversity of particle swarm. In addition, the Cauchy perturbation is used to avoid the algorithm from falling into local optimum. Finally, the adaptability function is formulated by comprehensively considering the performance constraints of the flight target as well as the UAV itself, which improves the accuracy of the evaluation model.

This study aims to explore the critical application areas of radio frequency identification (RFID) technology for sustainable buildings.

The quantitative research approach was adopted through a structured questionnaire administered to relevant stakeholders of construction projects. The data collected were analysed with the exploratory factor analysis, relative importance index (RII) and fuzzy synthetic evaluation (FSE).

The study’s results have categorised the crucial areas of application where construction industry stakeholders should focus their attention. These areas are divided into four categories: management technologies, production technologies, sensing technologies and monitoring technologies. The findings from the FSE indicate that monitoring technologies represent the most significant category, whereas management technologies rank as the least significant. Moreover, the RII analysis highlights that tools management stands out as the most important application of RFID, while dispute resolution emerges as the least significant RFID application.

The study establishes the core areas of RFID application and their benefits to sustainable buildings. Consequently, it helps stakeholders (consultants, clients and contractors) to examine the RFID application areas and make informed decision on sustainable construction. Furthermore, it provides systematic proof that can aid the implementation of RFID in developing countries.

The study provides an insight into the possible application areas and benefits of RFID technology in the construction industry of developing countries. It also developed a conceptual frame for the critical application areas of RFID technology in the construction industry of developing countries.

The recent pandemic disrupted the way in which businesses transact with each other. In response to maintaining cleanliness in business-to-business (B2B) settings, artificial intelligence (AI)-enabled robots have been adopted as substitutes for cleaning personnel, yet their implications remain largely underexamined. This study aims to examine B2B buyer responses to cleaning information notices (human vs AI-enabled agent) placed at either the entry to the premises or the sales counter, thereby adding to the nascent literature in this line of inquiry.

Three field experiments were conducted across diverse B2B businesses (wholesalers in Studies 1–2 and a commercial business in Study 3). To achieve greater empirical rigor and generalizability, this research used diverse stimuli across different B2B settings. In addition, the results ruled out alternate explanations and shed light upon political ideology as a boundary condition. Finally, a single-paper meta-analysis confirmed H1, consolidating the established effect.

Featuring over 1,000 B2B buyers, the results show that politically liberal B2B buyers express greater preference for human over AI-performed cleaning while labor-orientated buyers are indifferent. Importantly, this effect is driven by greater relaxation associated with humans, which in turn, increases their future patronage and referral intent.

The results enrich the collective knowledge of the adoption of AI-enabled robots, reinforcing for marketing practitioners and businesses that the reliance on human-based outcomes remains a preferred touchpoint in B2B settings, particularly for liberals.