Chunlan Li, Jun Wang, Min Liu, Desalegn Yayeh Ayal, Qian Gong, Richa Hu, Shan Yin and Yuhai Bao
Extreme high temperatures are a significant feature of global climate change and have become more frequent and intense in recent years. These pose a significant threat to both…
Abstract
Purpose
Extreme high temperatures are a significant feature of global climate change and have become more frequent and intense in recent years. These pose a significant threat to both human health and economic activity, and thus are receiving increasing research attention. Understanding the hazards posed by extreme high temperatures are important for selecting intervention measures targeted at reducing socioeconomic and environmental damage.
Design/methodology/approach
In this study, detrended fluctuation analysis is used to identify extreme high-temperature events, based on homogenized daily minimum and maximum temperatures from nine meteorological stations in a major grassland region, Hulunbuir, China, over the past 56 years.
Findings
Compared with the commonly used functions, Weibull distribution has been selected to simulate extreme high-temperature scenarios. It has been found that there was an increasing trend of extreme high temperature, and in addition, the probability of its indices increased significantly, with regional differences. The extreme high temperatures in four return periods exhibited an extreme low hazard in the central region of Hulunbuir, and increased from the center to the periphery. With the increased length of the return period, the area of high hazard and extreme high hazard increased. Topography and anomalous atmospheric circulation patterns may be the main factors influencing the occurrence of extreme high temperatures.
Originality/value
These results may contribute to a better insight in the hazard of extreme high temperatures, and facilitate the development of appropriate adaptation and mitigation strategies to cope with the adverse effects.
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Won-Suk Liu and Young-Min Choi
This paper introduces a monopolistic competition model containing retail investors with imperfect knowledge and issuers offering complex structured products. The model, for which…
Abstract
This paper introduces a monopolistic competition model containing retail investors with imperfect knowledge and issuers offering complex structured products. The model, for which we provide empirical evidences supporting the issuer’s profiteering by increasing the product complexity, can explain that knowledge asymmetry is the key for the issuer to offer complex product and to enjoy the higher excess profit, thus worsening allocative efficiency. Our empirical analysis reports monotonically increasing mark-up premia, and J-shaped issue amounts with respect to complexity: the former result could be explained in a rational framework considering issuer costs, however, the latter is not the case. Our model proves the empirical results are well explained when knowledge asymmetry between issuer and investors is a strictly increasing convex function of complexity.
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Xuemei Li, Ya Zhang and Kedong Yin
The traditional grey relational models directly describe the behavioural characteristics of the systems based on the sample point connections. Few grey relational models can…
Abstract
Purpose
The traditional grey relational models directly describe the behavioural characteristics of the systems based on the sample point connections. Few grey relational models can measure the dynamic periodic fluctuation rules of the objects, and most of these models do not have affinities, which results in instabilities of the relational results because of sequence translation. The paper aims to discuss these issues.
Design/methodology/approach
Fourier transform functions are used to fit the system behaviour curves, redefine the area difference between the curves and construct a grey relational model based on discrete Fourier transform (DFTGRA).
Findings
To verify its validity, feasibility and superiority, DFTGRA is applied to research on the correlation between macroeconomic growth and marine economic growth in China coastal areas. It is proved that DFTGRA has the superior properties of affinity, symmetry, uniqueness, etc., and wide applicability.
Originality/value
DFTGRA can not only be applied to equidistant and equal time sequences but also be adopted for non-equidistant and unequal time sequences. DFTGRA can measure both the global relational degree and the dynamic correlation of the variable cyclical fluctuation between sequences.
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Amer Jazairy, Emil Persson, Mazen Brho, Robin von Haartman and Per Hilletofth
This study presents a systematic literature review (SLR) of the interdisciplinary literature on drones in last-mile delivery (LMD) to extrapolate pertinent insights from and into…
Abstract
Purpose
This study presents a systematic literature review (SLR) of the interdisciplinary literature on drones in last-mile delivery (LMD) to extrapolate pertinent insights from and into the logistics management field.
Design/methodology/approach
Rooting their analytical categories in the LMD literature, the authors performed a deductive, theory refinement SLR on 307 interdisciplinary journal articles published during 2015–2022 to integrate this emergent phenomenon into the field.
Findings
The authors derived the potentials, challenges and solutions of drone deliveries in relation to 12 LMD criteria dispersed across four stakeholder groups: senders, receivers, regulators and societies. Relationships between these criteria were also identified.
Research limitations/implications
This review contributes to logistics management by offering a current, nuanced and multifaceted discussion of drones' potential to improve the LMD process together with the challenges and solutions involved.
Practical implications
The authors provide logistics managers with a holistic roadmap to help them make informed decisions about adopting drones in their delivery systems. Regulators and society members also gain insights into the prospects, requirements and repercussions of drone deliveries.
Originality/value
This is one of the first SLRs on drone applications in LMD from a logistics management perspective.
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Qingdan Jia, Xiaoyu Xu, Minhong Zhou, Haodong Liu and Fangkai Chang
This study embraces the call for exploring the determinants of continuous intention in TikTok. Taking the perspective of social influence, this study not only tries to explore the…
Abstract
Purpose
This study embraces the call for exploring the determinants of continuous intention in TikTok. Taking the perspective of social influence, this study not only tries to explore the contextual sources of two types of social influence but also aims to unveil the influence mechanism of how social influence affects TikTok viewers’ continuous intention.
Design/methodology/approach
This study empirically analyzes how TikToker attractiveness, co-viewer participation, platform reputation and content appeal affect informative and normative social influence and then lead to the continuous intention of TikTok. Based on 547 valid survey data, this study adopts a mixed analytical approach for data analysis by integrating structural equation modeling (SEM) and fuzzy-set qualitative comparative analysis (fsQCA).
Findings
SEM results unveil that content appeal is the most critical antecedent of informational social influence, while the TikToker attractiveness and platform reputation have no effect on it. Differently, all four external sources positively lead to normative social influence. Among them, content appeal and co-viewer participation influence the most. The influences of both two types of social influence on continuous intention are demonstrated. FsQCA results reveal seven alternative configurations that are sufficient for influencing continuance intention and further complement and reinforce the SEM findings.
Originality/value
Addressing the critical contextual elements of TikTok, this study explores and confirms the sources which may engender social influence. The authors also demonstrate the critical role of social influence in affecting TikTok viewers’ continuous intentions by the hybrid analytical approach, which contributes to existing academic literature and practitioners.
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Syed Shah Alam, Mohammad Masukujjaman, Samiha Susmit, Sumaiya Susmit and Hassanuddeen Abd Aziz
This study evaluated the determinants of augmented reality (AR) adoption in Malaysia's travel and tour operator sectors through an integrated technology-organization-environmental…
Abstract
Purpose
This study evaluated the determinants of augmented reality (AR) adoption in Malaysia's travel and tour operator sectors through an integrated technology-organization-environmental (TOE) and diffusion of innovation (DOI) model.
Design/methodology/approach
The TOE and DOI were considered the primary theoretical models but are combined and extended by including few additional variables. Data were collected from 220 respondents of travel and tour operating businesses in Malaysia and analyzed by applying PLS structural equation model technique.
Findings
The empirical results established that perceived cost, relative advantages, complexity and compatibility, observability, competitor pressure, value alignment, customer pressure, and trialability are positively connected with the behavioral intention except for external support. The results reveal that value alignment partially mediates the association between relative advantages and behavioral intention, complexity and behavioral intention, compatibility and behavioral intention, perceived cost and behavioral intention except in between trialability and observability.
Originality/value
This research is unique as the value alignment construct is included in the model, and thus it fulfills the literature gap by adding the mediation construct. This study contributes to enhancing AR's understanding of the Malaysian travel and tour operator industry through the lenses of owners or managers. It offers an integrated model that combines the TOE and DOI models, rare in this sector, and can be replicated or extended with validated scales.
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This paper examines the comparative corporate performance of logistics companies in Korea, China and Japan. Based on the annual data from the listed companies, the growth rate of…
Abstract
This paper examines the comparative corporate performance of logistics companies in Korea, China and Japan. Based on the annual data from the listed companies, the growth rate of Chinese companies has surpassed that of Korean and Japanese companies and has labeled China as the fastest growing economy. How ever, labor efficiency of Chinese firms when calculated by total revenue per employee is the lowest of the three countries. In addition, the profitability of Chinese multimodal logistics companies and sea transport companies is also lower than that of Korea and Japan.
Using Data Envelop Analysis(DEA), the primary results regarding corporate efficiency among Korean, Chinese and Japanese logistic companies are as follows: In the multimodal industries, Japanese firms have revealed the highest level of efficiency, with Korean firms coming in second, and Chinese firms ranking third with distinctly inferior performance. This trend has also been examined in the maritime industries, in which the efficiency levels have been deteriorating continuously. However, in the air transportation industry Chinese companies revealed the highest level of efficiency, which resulted from the business characteristics of the government supported conglomerate companies.
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Ward Van Zoonen, Jeffrey W. Treem and Anu Sivunen
The benefits associated with visibility in organizations depend on employees' willingness to engage with technologies that utilize visible communication and make communication…
Abstract
Purpose
The benefits associated with visibility in organizations depend on employees' willingness to engage with technologies that utilize visible communication and make communication visible to others. Without the participation of workers, enterprise social media have limited value. This study develops a framework to assess what deters and drives employees' use of enterprise social media.
Design/methodology/approach
Data were collected from 753 employees of a global company using an online survey. The response rate was 24.5%. The authors used structural equation modeling to test the hypothesized framework.
Findings
The results show that various fears by workers may deter or motivate enterprise social media use. This offers an alternative viewpoint for examining the consequences of communication visibility in organizations. Specifically, the findings demonstrate that the fear of accountability and the fear of losing uniqueness reduce enterprise social media use through increased codification efforts. The fear of missing out is directly and positively related to collecting behaviors on enterprise social media.
Research limitations/implications
Expectations about participation in visible organizational communication environments are rising. However, as individuals may experience anxiety in such settings, the authors need to direct more analytical focus to the ways individuals manage communication visibility in organizing contexts and develop a deeper understanding of the consequences of fear in workplace communication.
Originality/value
The analysis recognizes that fear can play a key role in deterring or motivating workers' specific choices in navigating the challenges that occur when technology can make communication broadly visible. This study uses theorizing on communication visibility to bring together different fear mechanisms to predict enterprise social media use.
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Yixin Zhang, Lizhen Cui, Wei He, Xudong Lu and Shipeng Wang
The behavioral decision-making of digital-self is one of the important research contents of the network of crowd intelligence. The factors and mechanisms that affect…
Abstract
Purpose
The behavioral decision-making of digital-self is one of the important research contents of the network of crowd intelligence. The factors and mechanisms that affect decision-making have attracted the attention of many researchers. Among the factors that influence decision-making, the mind of digital-self plays an important role. Exploring the influence mechanism of digital-selfs’ mind on decision-making is helpful to understand the behaviors of the crowd intelligence network and improve the transaction efficiency in the network of CrowdIntell.
Design/methodology/approach
In this paper, the authors use behavioral pattern perception layer, multi-aspect perception layer and memory network enhancement layer to adaptively explore the mind of a digital-self and generate the mental representation of a digital-self from three aspects including external behavior, multi-aspect factors of the mind and memory units. The authors use the mental representations to assist behavioral decision-making.
Findings
The evaluation in real-world open data sets shows that the proposed method can model the mind and verify the influence of the mind on the behavioral decisions, and its performance is better than the universal baseline methods for modeling user interest.
Originality/value
In general, the authors use the behaviors of the digital-self to mine and explore its mind, which is used to assist the digital-self to make decisions and promote the transaction in the network of CrowdIntell. This work is one of the early attempts, which uses neural networks to model the mental representation of digital-self.
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Jonathan Atta-Aidoo, Saidi Bizoza, Ester Cosmas Matthew and Abdulkarim Onah Saleh
Attaining the Sustainable Development Goal 2 (SDG2) of zero hunger continues to be a challenge in most parts of Sub-Saharan Africa. However, financial inclusion is seen as a…
Abstract
Purpose
Attaining the Sustainable Development Goal 2 (SDG2) of zero hunger continues to be a challenge in most parts of Sub-Saharan Africa. However, financial inclusion is seen as a potential pathway for reducing food insecurity among poor households. Mobile money is a financial inclusion instrument that is easily accessible to poor households and has the potential to increase the level of financial inclusion. This paper contributes to the literature by examining the determinants of mobile money adoption, its effects on household food security and the choice of coping strategies in Burundi, a post-conflict and fragile country.
Design/methodology/approach
Using survey data that involved 860 households in Burundi, we adopted the Household Hunger Scale (HHS) developed under the Food and Nutrition Technical Assistance Project to measure household food security. We further employ the endogenous switching regression treatment effects model for ordered outcomes and the multivariate probit model to achieve our aims.
Findings
The results of our study reveal that the adoption of mobile money is influenced by factors such as gender, marital status, age, formal education, membership in a social network, area of residence and access to a tarred road network. Additionally, the food security status of a household was determined by marital status, formal education, social network membership, access to tarred roads, off-farm income, access to credit and land tenure security. We confirm that mobile money adoption has a significantly positive effect on the food security status of households with heterogeneity in gender and area of residence. We also find that mobile money adoption reduces the likelihood of households adopting consumption-related coping strategies.
Practical implications
The promotion of mobile money should, therefore, be included in Burundi’s national food security policies.
Originality/value
This study contributes to the literature by providing empirical evidence on the effect of mobile money adoption on household food security and the choice of coping strategies in a post-conflict context.