Advancements in technology have revolutionized communication, socialization, and work paradigms. The surges in globalization, the permeation of digital culture, and the expansion of online communication tools have prompted organizations globally to adopt virtual teams. These virtual environments, while beneficial, present a myriad of challenges that necessitate the application of system dynamics to optimize performance. A systematic review was conducted to analyze previous studies focusing on the leadership of virtual teams within the context of systems thinking. Seven databases, including Sage Online, Springer, JSTOR, Taylor and Wiley Online Library, Francis Online, Google Scholar, and Semantic Scholar, were utilized. From an initial pool of 5,070 studies, 30 were meticulously screened, summarized, and synthesized based on pre-established inclusion and exclusion criteria. The review highlighted the recurrent emphasis on factors such as communication technology, trust, intra-team relationships, and leadership strategies as pivotal for enhancing virtual team performance. This synthesis aims to present a comprehensive overview of current research trajectories in the field, delineating existing research gaps, limitations, and challenges.
Disruptive technologies such as the big data analytics, blockchain, Internet of Things, and artificial intelligence have each impacted how businesses operate. The most recent example of disruptive technology is artificial intelligence (AI), which has the most potential to revolutionize marketing completely. Practitioners worldwide are searching for artificial intelligence (AI) solutions most suited for their marketing functions. Artificial intelligence can provide marketers with assistance in a variety of ways to boost client satisfaction. This article looks at the exciting new developments in artificial intelligence (AI) and marketing that have been occurring recently, it examines the latest developments in marketing using artificial intelligence (AI). These breakthroughs encompass predictive analytics for analyzing customer behaviour, integrating chatbots to enhance customer support, and implementing AI-driven content personalization tactics. This article also covers the horizons and problems of artificial intelligence and marketing, the precise applications of AI in a range of marketing segments, and their impact on marketing sectors. Additionally, this article examines the particular applications of AI in marketing.
In decision-making scenarios, challenges often arise from closely knitted criteria or inherent uncertainties. Such uncertainties prominently pervade the realm of sustainable energy, particularly concerning hydrogen generation systems. A critical need is identified to elucidate the efficiency, costs, and environmental implications of these technologies as a shift towards a low-carbon economy is pursued. In this study, the interdependencies among decision-making variables were examined, revealing their collective influence and correlations. By utilizing the framework of Intuitionistic Hypersoft Sets (IHSSs), uncertainties were addressed, multi-criteria decision-making (MCDM) was harnessed, technological selection was facilitated, resource allocation was optimized, and environmental ramifications were assessed. The primary objective of this research was to decipher the conundrum of choosing among multiple hydrogen production methodologies. Such an approach fosters the adoption of environmentally conducive hydrogen production methods, heralding a shift towards a greener energy future. Notably, further research could probe into methodologies like AHP and TOPSIS in a neutrosophic context, offering tantalizing avenues for exploration.
This study addresses the challenge of selecting appropriate electric vehicles for urban logistics, with a specific focus on the impact of various multi-criteria analysis methods on this complex decision-making process. The investigation utilizes a mixed methodology, combining objective weight determination methods, such as Entropy, CRITIC (Criteria through the Inter-Criteria Correlation), and MEREC (Method Based on the Removal Effects of Criteria), alongside standard deviation and a modified version of the standard deviation method. The Simple Additive Weighting (SAW) method was further employed for alternative ranking. Application of these methods across nine diverse Small Van vehicles, assessed according to 12 criteria, highlighted the paramountcy of Charge Time and Cargo Volume as factors bearing the most significant weight in decision-making. The Toyota Proace City Verso Electric L2 emerged as a superior choice under most conditions. Yet, the results varied when applying weights deduced through the MEREC method, leading to the ascendency of the Renault Kangoo E-Tech. The study underscores that the objective determination of criteria weights plays an influential role in the ranking of alternatives, hence, the requirement for decision-makers' subjectivity in the final choice, factoring in the unique attributes of individual companies. This research contributes to the understanding of how multi-criteria analysis can facilitate electric vehicle selection for urban logistics, playing a crucial part in reducing harmful urban emissions.
This study presents an in-depth investigation of watermelon cultivation in Bangladesh, focusing on the assessment of production levels, costs, influential factors, and the application of Fuzzy Cognitive Map (FCM) technology for precision agriculture. Utilizing degree centrality and closeness centrality measures, the FCM model is employed to systematically examine the interplay among various elements involved in watermelon cultivation in Bangladesh and to elucidate the impacts of these factors on production yield. The findings contribute to the advancement of precision agriculture practices and provide valuable insights for optimizing watermelon production management in Bangladesh.
The interrelation between logistics and international trade is crucial for understanding a country's ability to increase its share in global trade. An adequate and well-integrated logistics sector and infrastructure are required for this purpose. This study employs the novel Multi-Criteria Decision Analysis (MCDA) approach known as REF-III and two distinct models to investigate the activities of countries in terms of infrastructure, logistics, international trade, and economic growth. The results from both models indicate that China and Russia are leading the rankings. However, when focusing on the efficiency of trade and economic growth, the United States occupies the first place. Notably, several Caucasian and Balkan countries rank poorly in both models, possibly due to the multiple crises, wars, and turmoil they have experienced over the past forty years. The investments and improvements made in infrastructure and logistics by the countries excelling in global trade and logistics should serve as a model for other nations to emulate.
With the growing need for digital business transformation, corporate venture capital (CVC) investors have been faced with the challenge of how to deal with this trend. Although digital business transformation and CVC are highly relevant, previous studies have investigated them separately instead of their relationships. Therefore, this research aimed to study the impact of CVC on digital business transformation to fill this research gap. Based on an exploratory research design, eleven experts from different industries were interviewed. The following results were found in this study: (1) after the CVC unit collaborated with an Open Innovation (OI) unit, the CVC activities were integrated into the decentralized OI activities, and a dedicated team in the CVC unit was responsible for OI and venture client-based OI activities, thus achieving digital OI; (2) CVC was used to pursue ambidexterity, digital exploration or exploitation; (3) CVC supported digital business transformation at the organizational, social, and technical levels, which provided an answer to the overarching research question of how CVC supported innovation processes. Theoretical implications of this study lied in enhancing the understanding between CVC and digital business transformation, thus extending the understanding of CVC organization and impact. Furthermore, this study provided practical implications and recommendations on organizing CVC and using it to achieve digital business transformation according to strategic objectives.
Responsible use of social media requires a level of culture and awareness on the part of the user themselves that allows them to understand and absorb the enormous amount of information they receive through these mediums, verify it, and then share it with their friends and users. This leads to numerous problems related to public health and safety. This research aims to identify the most significant effects of the dissemination of fake news in times of crisis on public health and safety, as well as to propose strategies to overcome this phenomenon. A hybrid Grey-ARAS (Additive Ratio Assessment) model was used to rank the potential impacts and propose strategies to overcome them. Four experts in the field of public health, data analysis, and contagious diseases participated in this study to determine the weights. Eight factors affecting public health and safety were proposed, along with seven strategies to mitigate these impacts. The results showed that the most important factors are creating panic and anxiety among people along with the contribution to the misleading public policy decisions. The results also showed that the most appropriate strategies to overcome the impact of fake news are to encourage people to check facts and monitor social media. A sensitivity analysis of the results obtained was also performed, proposing 20 different scenarios to adjust the relative weights of the criteria. The results showed a certain stability when using different scenarios.
As environmental awareness grows, consumers' green and low-carbon preferences have become essential factors for market enterprises to consider in decision-making. This paper conducts a literature review of dual-channel supply chain pricing decisions under the influence of consumers' low-carbon preference. The analysis is carried out from two aspects: dual-channel supply chain types and consumers' low-carbon preference. By combining psychological games and analyzing relevant literature, this paper provides insights into the factors that affect consumers' low-carbon preference and explores the synergies among various factors, including government policies. Moreover, this paper suggests future research directions, such as conducting empirical research on relevant models, to support the diversified development of the dual-channel field.
This study applies the FMEA-QFD approach to assess risks in the distribution process, with a focus on warehouse and transport processes, which are commonly associated with user dissatisfaction and customer loss. The methodology identifies the forms, effects, and causes of failures and determines priorities for each category. In that manner, for the warehousing process, long reception time, additional costs, and lack of experience have the highest priority. In the transportation process, time losses, generating additional costs, and longer vehicle retention time are the three failure effects with the highest priorities. Corrective and preventive measures are also defined. The proposed approach is highly applicable in practice and can be modified for use in other industries. This paper contributes both theoretically and practically to the field of logistics.
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