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The post-pandemic crisis has reshaped work dynamics across industries, leading to a widespread reliance on technology for remote work and business continuity. Operations have shifted to the digital space, altering job requirements and creating new career opportunities. The expansion of the digital industry has generated numerous career choices. The purpose of this study is to determine the relationships between self-efficacy, social media, career outcome expectations and career choices among fresh graduates in Malaysia amid the pandemic crisis.

Research data were collected from a sample of 318 fresh graduates from both public and private universities in Malaysia. Partial least squares structural equation modeling (PLS-SEM) was used to analyze the data in this study.

The empirical findings revealed significant correlations between self-efficacy, social media usage and career outcome expectations and the career choices of Malaysian fresh graduates.

The present study offers an empirical framework to explain career choices among fresh graduates in Malaysia during the pandemic crisis, based on a review of related literature on careers. This research contributes to the body of knowledge on career choices among Generation Z fresh graduates and provides practical implications for organizations and individual employees. It suggests developing relevant Human Resource Development (HRD) interventions to retain the young workforce within organizations.

This study enriches the existing literature on self-efficacy, social media and career outcome expectations in the context of a pandemic crisis. It offers a new interpretation of how individual and contextual factors impact career choices, shaping the career management attitudes of fresh graduates in the post-pandemic era. The empirical findings also give valuable insights into higher education institutions, organizations and government authorities in Malaysia to develop relevant interventions to assist undergraduate students in their career choice exploration.

Unsafe food consumption results in adverse health conditions, foodborne illness and undernutrition among households and communities. The consumption of food contaminated with harmful microorganisms or with harmful pesticide residuals results in adverse health conditions and undernutrition. However, there are a number of challenges to maintaining food safety in the food systems of developing countries, like Nepal, where awareness of food safety is low and research on these issues is lacking.

We conducted an experiment among youth aged between 20 and 26 years in Nepal to assess their food safety awareness and affinity to safer fresh produce choices. In the classroom setting experimentations with and without information nudges conducted among 224 youth participants, participants chose one fresh produce packet among the four. We analyzed results using multinomial and mixed logit models appropriate for discrete choice modeling.

We found that the youth’s perceived higher importance of sustainable food systems and their knowledge levels on microbial contamination and foodborne illnesses play significantly positive roles. The likelihood of choosing microbial safety-labeled fresh produce or both microbial- and chemical safety-labeled fresh produce increased with nudging among those who have some knowledge of microbial contamination and foodborne illnesses – we found that the interaction of nudging and level of knowledge is significantly positive. Youth belonging to higher income classes do not necessarily have a higher affinity to safer fresh produce but with nudging, the higher income class youth have a higher likelihood of choosing safer fresh produce choices.

Youth engagement and their awareness of food safety could be one of the important strategies to potentially develop them as effective promoters, adopters and educators in enhancing food safety in food systems in Nepal. Our predicted premium for food safety attributes points to the potential scope for the emerging market segment or business opportunities augmenting food safety in Nepal.

We examined the factors influencing the safer fresh produce choices among youth in Nepal. We tested whether awareness levels of microbial contamination and foodborne illness and information nudging affect the likelihood of safer fresh produce choice. Then we predicted the willingness to pay (premium) for safety attributes. To the best of our knowledge, none of the previous studies have examined this aspect in Nepal.

While designing personally meaningful activities with data technologies can support the development of data literacies, this paper aims to focuses on the overlooked aspect of how learners navigate tensions between personal experiences and data trends.

The authors report on an analysis of three student cases from a design study in which middle and high school youth assembled family migration stories using data visualization technologies with socioeconomic and demographic data. The authors used interaction analysis to examine how students responded to misalignments they encountered between their families’ experiences and data trends in their models, drawing on the theoretical construct of epistemic data agency.

This case analysis demonstrates ways in which students enacted epistemic data agency. Instructional support can help students deepen inquiry and avoid certain pitfalls, such as encoding data in unsound or misleading ways to support a particular story, while encouraging students to see themselves as an epistemic authority on par with data. This study opens pathways for future research that considers how data can shape personal narratives and how students can leverage their experiences in the stories they tell with data.

The authors introduce the construct of epistemic data agency to describe the conceptual and material practices that reveal and shape students’ relationships to the data. The descriptions of students enacting epistemic data agency in assembling data stories informs the understanding of how to better elevate and recognize students’ efforts in relation to disciplinary norms and support deeper, meaningful student learning with and about data.

The purpose of this paper is to emphasize the risks involved in modeling inflation volatility in the context of macroeconomic policy. For countries like Ghana that are always battling economic problems, accurate models are necessary in any modeling endeavor. We estimate volatility taking into account the heteroscedasticity of the model parameters.

The estimations considered the quasi-maximum likelihood-based GARCH, stochastic and Bayesian inference models in estimating the parameters of the inflation volatility.

A comparison of the stochastic volatility and Bayesian inference models reveals that the latter is better at tracking the evolution of month-on-month inflation volatility, thus following closely the data during the period under review.

The paper looks at the effect of parameter uncertainty of inflation volatility alone while considering the effects of other key variables like interest and exchange rates that affect inflation.

Economists have battled with accurate modeling and tracking of inflation volatility in Ghana. Where the data is not well-behaved, for example, in developing economies, the stochastic nature of the parameter estimates should be incorporated in the model estimation.

Estimating the parameters of inflation volatility models is not enough in a perpetually gyrating economy. The risks of these parameters are needed to completely describe the evolution of volatility especially in developing economies like Ghana.

This work is one of the first to draw the attention of policymakers in Ghana towards the nature of inflation data generated in the economy and the appropriate model for capturing the uncertainty of the model parameters.

Internet search is a $120bn business that answers lists of search terms or keywords with relevant links to Internet webpages. Only a few companies have sufficient scale to compete and thus economics of the process are paramount. This study aims to develop a detailed industry-specific modeling of the economics of internet search.

The current research develops a stochastic model of the process of Internet indexing, search and retrieval in order to predict expected costs and revenues of particular configurations and usages.

The models define behavior and economics of parameters that are not directly observable, where it is difficult to empirically determine the distributions and economics.

The model may be used to guide the economics of large search engine operations, including the advertising platforms that depend on them and largely fund them.

This study aims to conduct a bibliometric analysis on “intertemporal choice” behavior of individuals from journals in the Scopus database between 1957 and 2023. The research covered the data on the said topic since it first originated in the Scopus database and carried out performance analysis and content analysis of papers in the business management and finance disciplines.

Bibliometric analysis, including science mapping and performance analysis, followed by content analysis of the papers of identified clusters, was conducted. Three clusters based on cocitation analysis and six themes (three major and three minor) were identified using the bibliometrix package in R studio. The content analysis of the papers in these clusters and themes have been discussed in this study, along with the thematic evolution of intertemporal choice research over the period of time, paving a way for future research studies.

The review unpacks publication and citation trends of intertemporal choice behavior, the most significant authors, journals and papers along with the major clusters and themes of research based on cocitation and degree of centrality and relevance, respectively, i.e. discounting experiments and intertemporal choice, impulsivity, risk preference, time-inconsistent preference, etc.

Over the past years, the research on “intertemporal choice” has flourished because of the increasing interest of researchers and scholars from different fields and the dynamic and pervasive nature of this topic. The well-developed and scattered body of knowledge on intertemporal choice has led to the need of applying a bibliometric analysis in the intertemporal choice literature.

How do informal lending institutions affect entrepreneurship? This paper aims to investigates the role of formal and informal credit market institutions in the decision to become an entrepreneur over the life cycle.

The author developed a dynamic Roy model in which a decision to become an entrepreneur depends on the access to formal and informal credit markets, nonpecuniary benefits of entrepreneurship, career-specific entry costs, prior work experience, education, unobserved abilities and other labor market opportunities (salaried employment and nonemployment). Using detailed Russian panel microdata (the Russia longitudinal monitoring survey) and estimating a structural model of labor market decisions and borrowing options, the author assesses the impact of the development of informal and formal credit institutions.

The expansion of traditional (formal) credit market institutions positively impacts all workers’ categories, reduces the share of entrepreneurs who borrow from informal sources and incentivizes low-type entrepreneurs to switch to salaried employment. The development of the informal credit market reduces the percentage of high-type entrepreneurs who borrow from formal sources. In the case of default, a higher value of the social network or higher costs of losing social ties demotivate low-type entrepreneurs to borrow from informal sources. The author highlights the practical implications of estimates by evaluating policies designed to promote entrepreneurship, such as subsidies and accessibility regulations in credit market institutions.

This study contributes to the literature in several ways. Unlike other studies that focus on individual characteristics in the selection for self-employment [Humphries (2017), Hincapíe (2020), Gendron-Carrier (2021), Dillon and Stanton (2017)], the paper models labor and borrowing decisions jointly. Previous studies discuss transitions between salaried employment and self-employment, taking into account entrepreneurial earnings, wealth, education and age, but do not consider the availability of financial institutions as a driving factor for the selection into self-employment. To the best of the author’s knowledge, this paper shows for the first time that the transition from salaried employment to self-employment is standard and consistent with changes in access to financial institutions. Another feature of this study is incorporating both types of credit markets – formal and informal. The survey by the European Central Bank on the Access to Finance of Enterprises (2018) shows 18% of small and medium enterprise in EU pointed funds from family or friends. Therefore, the exclusion from consideration of informal credit markets may distort the understanding of the role of the accessibility of credit markets.

Choosing the proper selling format for online retail has long been a critical issue for many platforms to consider, whereas the emergence and popularity of live-streaming have had a massive impact on the platform's business. As a result, selecting the suitable operating strategy for the live channel has become another critical issue for platforms. In such a context, what will be the impact of live-streaming on selling formats?

In order to explore these issues, we identified two selling formats (wholesale reselling or agency selling) as well as two operating strategies (introduce or discard). Thereby, four channel-structures are constructed, namely the reselling-discard model (WN), the reselling-introduce model (WL), the agency-discard model (AN), and the agency-introduce model (AL). We comprehensively compare how different structures affect stakeholders' interests, consumer surplus, and social welfare through equilibrium analyses.

These results help clarify the impact of critical factors (e.g. self-effort attribute, cross-effort attribute, and commission ratio) on the choice of models. We find that regardless of the selling agreement between the manufacturer and the platform, the introduction of a live store is necessary; specifically, when the commission ratio is high, the platform's optimal decision is first to sign an agency agreement and then apply live selling (AL); conversely, when the commission ratio is low, the platform's optimal strategy is first to enable the live channel and then to select the reselling format (WL), together, this also reveals, from a theoretical perspective.

Our study includes the dual analysis of selling formats and channel operations, considering the inherent dual attributes of service efforts and the external competitive environment.

This paper aims to explore the outcomes of an analysis on day by day task – journey planning conduct of senior citizens by using a modern dynamic model and a family unit travel overview, gathered in Bhubaneswar, Odisha, of India in 2018. The task-journey planning display assumes an unique time–space-constrained planning development.

The main commitment of this paper is to reveal day by day task – journey planning conduct through a comprehensive dynamic framework. Numerous behavioural subtleties are revealed by the subsequent empirical model. These incorporate the role that income plays in directing outside time consumption decisions of senior citizens. Senior citizens in the most elevated and least salary classes will in general have minor varieties in time consumption decisions than those in middle pay classifications. Generally speaking, the time consumption decisions become progressively steady with expanding age, demonstrating that more task durations and lower task recurrence become progressively predominant with increasing age.

Day by day task-type and area decisions reveal a reasonable irregular utility-amplifying level headed conduct of senior residents. Unmistakably expanding spatial availability to different task areas is an urgent factor in characterizing every day outside task interest of senior residents. It is likewise evident that the assorted variety of outside task-type decisions decreases with rise in age and senior citizens are major touchy to auto journey hour than to travel or non-mechanized journey hour.

The fundamental constraint to the dynamic structure is that the mode decision model was viewed as exogenic to the demonstrating framework. The essential purpose behind this supposition that was that senior citizens in the Bhubaneswar are overwhelmingly customers of the local car. Coordination of the mode decision display part inside this structure would deliver a full task-based journey request model that could catch trip age, starting times, outing circulation and mode decision using a solitary demonstrating framework.

The aim of this study is to (1) construct a standard framework for assessing the capability of bioenergy enterprises' digital green innovation partners; (2) quantify the choice of partners for digital green innovation by bioenergy enterprises; (3) propose based on a dual combination empowerment niche digital green innovation field model.

Fuzzy set theory is combined into field theory to investigate resource complementarity. The successful application of the model to a real case illustrates how the model can be used to address the problem of digital green innovation partner selection. Finally, the standard framework and digital green innovation field model can be applied to the practical partner selection of bioenergy enterprises.

Digital green innovation technology of superposition of complementarity, mutual trust and resources makes the digital green innovation knowledge from partners to biofuels in the enterprise. The index rating system included eight target layers: digital technology innovation level, bioenergy technology innovation level, bioenergy green level, aggregated digital green innovation resource level, bioenergy technology market development ability, co-operation mutual trust and cooperation aggregation degree.

This study helps to (1) construct the evaluation standard framework of digital green innovation capability based on the dual combination empowerment theory; (2) develop a new digital green innovation domain model for bioenergy enterprises to select digital green innovation partners; (3) assist bioenergy enterprises in implementing digital green innovation practices.