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This research sought to examine the potential association between workers’ financial worry and counterproductive work behavior. Based on the basic psychological need theory, we propose that psychological need satisfaction explains this relationship and we position this volitional pathway as an alternative to a cognitive capacity pathway based on the cognitive load theory.

We conducted a two-week interval-lagged survey study with three measurement points among 180 US workers. The mediation models were tested using structural equation modeling.

The results support the conclusion that, while cognitive capacity could have an impact on counterproductive work behavior, its mediating effect is less strong than that of need satisfaction.

Based on the results, we recommend that organizations design their compensation and benefits system to shield employees from financial worries. At the same time, we advise offering the employees who do experience financial worries assistance in managing their budgets and offering other forms of financial coaching.

This study is innovative because we show that the negative effects of financial worry extend much further than initially thought and affect not only employees' cognition but also their motivation.

The increasing prevalence of a wide range of infectious diseases, as well as the underwhelming results of vaccination rates that may be traced back to problems with vaccine procurement and distribution, have brought to the fore the importance of vaccine supply chain (VSC) management in recent years. VSC is the cornerstone of effective vaccination; hence, it is crucial to enhance its performance, particularly in low- and middle-income countries where immunization rates are not satisfactory.

In this paper, the authors focus on VSC performance improvement of India by proposing supply contracts under demand uncertainty. The authors propose three contracts – wholesale price (WSP), cost sharing (CS) and incentive mechanism (IM) for the government-operated immunization program of India.

The authors' findings indicate that IM is capable of coordinating the supply chain, whereas the other two contracts are inefficient for the government. To validate the model, it is applied to a real-world scenario of coronavirus disease 2019 (COVID-19) in India, and the findings show that an IM contract improves the overall efficiency of the system by 23.72%.

Previous studies focused mainly on the influenza VSC industry within developed nations. Nonetheless, there exists a dearth of literature pertaining to the examination of supply contracts and their feasibility for immunization programs that are administered by the government and aimed at optimizing societal benefits. The authors' findings can be beneficial to the immunization program of India to optimize their VSC cost.

Economic ties and formation of trade blocks escalates the movement of goods among the participants and bring different economic and structural changes. Therefore, the current research emphasises on the distribution of market structure and industrial value added among the participant countries of China–Pakistan economic corridor project while focussing on pre and post FTA status.

This study utilises the footloose capital model for analysing whether China or Pakistan is more suitable for attracting factors of production to increase their share of industrial value added. For econometric analyses the current research utilises data from 1995 to 2018 and maximum likelihood effect method to assess factors that affect regional value-added distribution.

Results show that both countries owe different level of economic developments. Effect of capital is, comparatively, similar for both countries while Pakistan supports trade openness which points towards the fact of positive utilisation of abundant labour resources in Pakistan by establishing industrial structure either through domestic capital formation or foreign investment. Whereas, share of labour and trade openness of China positively affect value added production of China.

This is one of the unique studies that studies the regional economic treaties usefulness for any developing country across Asia. Where this study uses the footloose capital model and maximum likelihood method for its analysis which is not previously done, while for detailed analyses the study further divides the timeframe into two parts as pre-FTA ranges from 1995 to 2006, post-FTA from 2007 to 2018 while overall results consist of whole-time frame.

The purpose of this paper is to cut down energy consumption and eliminate production waste on mixed-model assembly lines. Therefore, a supermarket integrated dynamic cyclic kitting system with the application of electric vehicles (EVs) is introduced. The system resorts to just-in-time (JIT) and segmented sub-line assignment strategies, with the objectives of minimizing line-side inventory and energy consumption.

Hybrid opposition-based learning and variable neighborhood search (HOVMQPSO), a multi-objective meta-heuristics algorithm based on quantum particle swarm optimization is proposed, which hybridizes opposition-based learning methodology as well as a variable neighborhood search mechanism. Such algorithm extends the search space and is capable of obtaining more high-quality solutions.

Computational experiments demonstrated the outstanding performance of HOVQMPSO in solving the proposed part-feeding problem over the two benchmark algorithms non-dominated sorting genetic algorithm-II and quantum-behaved multi-objective particle swarm optimization. Additionally, using modified real-life assembly data, case studies are carried out, which imply HOVQMPSO of having good stability and great competitiveness in scheduling problems.

The feeding problem is based on static settings in a stable manufacturing system with determined material requirements, without considering the occurrence of uncertain incidents. Current study contributes to assembly line feeding with EV assignment and could be modified to allow cooperation between EVs.

The dynamic cyclic kitting problem with sub-line assignment applying EVs and supermarkets is solved by an innovative HOVMQPSO, providing both novel part-feeding strategy and effective intelligent algorithm for industrial engineering.

The authors integrate social cognitive theory with social exchange theory to examine how subordinates' perceptions of leader-member exchange (LMX) and moral disengagement mediate the relationship between congruence on implicit leadership theories (ILTs) of ethical leaders and characteristics recognized in one's supervisor (ethical ILT–supervisor alignment) and subsequent engagement-related outcomes (engagement attitudes, job satisfaction and supervisor-directed deviance). The authors then examine romance of leadership (ROL) as a moderator of these relationships.

The authors tested the theorized indirect effects and boundary conditions in a moderated mediation model using 180 working adults over three time points, in a polynomial regression framework using a block variable approach.

The authors found moderated indirect effects between ethical ILT–supervisor alignment and work-related outcomes via LMX and moral disengagement. ROL served as a boundary condition, such that the high levels bolstered the positive effects of ethical ILT–supervisor alignment.

The study results suggest that examining ethical leadership through the lens of implicit theories may be fruitful and highlight the importance of accounting for context when assessing the impact of ILTs.

This study analyzes the role of migrant networks in the migration flows in relation to the educational level of the migrants and economic growth of the states of origin and destination in Brazil.

Fixed effects estimator applied to microdata.

The results show migrant networks have a significant and positive impact on migration flows of the different educational levels. The economic growth in the destination state accentuates this effect, while the economic growth in the origin state has distinct impacts according to the educational level of the new migrant.

The authors investigate the importance of migrant networks in the internal immigration within a developing country with large internal movement of people. In Brazil, the socio-economic condition of the population varies considerably in relation to its geography, which explains the country’s large internal migration flows.

The extant literature provides evidence that single CEOs are less risk-averse. Building on the theory of risk aversion, the authors argue that the risk aversion trait arising from CEO’s marital status partially explains capital allocation efficiency. The paper aims to examine the association between CEO marital status and capital allocation efficiency.

The primary sample includes 9,671 observations from 1,264 US firms. The authors apply multivariate regression and a series of endogeneity tests to examine the association between CEO marital status and capital allocation efficiency.

Single-CEO firms have higher capital allocation inefficiency than those with married CEOs. The findings continue to hold after a series of endogeneity tests such as propensity score matching, change analysis and instrumental variable regression analysis and are robust to alternative proxies for capital allocation inefficiency. The capital allocation inefficiency in single-CEO firms arises from overinvestment but not underinvestment, and corporate risk-taking channels the effect.

The study is limited to the effect of CEO marital status, not CEO marital quality.

The findings imply that besides information asymmetry and agency conflicts, CEO marital status should receive special attention for capital allocation efficiency. Also, marital status influences the CEOs’ commitment to the general good of society, affecting the potential conflict of interest with different stakeholders from inefficient capital allocation.

This study extends corporate finance literature on CEO marital status by providing novel evidence on the effect of single CEOs on capital allocation efficiency. The authors conclude that CEOs’ personality traits, such as marital status, matter in corporate policy choices.

Given inconsistent results in prior studies, this paper applies the dual process theory to investigate what social media messages yield audience engagement during a political event. It tests how affective cues (emotional valence, intensity and collective self-representation) and cognitive cues (insight, causation, certainty and discrepancy) contribute to public engagement.

The authors created a dataset of more than three million tweets during the 2020 United States (US) presidential elections. Affective and cognitive cues were assessed via sentiment analysis. The hypotheses were tested in negative binomial regressions. The authors also scrutinized a subsample of far-famed Twitter users. The final dataset, scraping code, preprocessing and analysis are available in an open repository.

The authors found the prominence of both affective and cognitive cues. For the overall sample, negativity bias was registered, and the tweet’s emotionality was negatively related to engagement. In contrast, in the sub-sample of tweets from famous users, emotionally charged content produced higher engagement. The role of sentiment decreases when the number of followers grows and ultimately becomes insignificant for Twitter participants with many followers. Collective self-representation (“we-talk”) is consistently associated with more likes, comments and retweets in the overall sample and subsamples.

The authors expand the dominating one-sided perspective to social media message processing focused on the peripheral route and hence affective cues. Leaning on the dual process theory, the authors shed light on the effectiveness of both affective (peripheral route) and cognitive (central route) cues on information appeal and dissemination on Twitter during a political event. The popularity of the tweet’s author moderates these relationships.

With the upgrade of natural language interaction technology, the simulation extension of intelligent voice assistants (IVAs) and the uncertainty of products and services have received more and more attention. However, most of the existing research focuses on investigating the application of theories to explain consumer behavior related to intention to use and adopt IVAs, while ignoring the impact of its privacy issues on consumer resistance. This article especially examines the negative impact of artificial intelligence-based IVAs’ privacy concerns on consumer resistance, and studies the mediating effect of perceived creepiness in the context of privacy cynicism and privacy paradox and the moderating effect of anthropomorphized roles of IVAs and perceived corporate social responsibility (CSR) of IVAs’ companies. The demographic variables are also included.

Based on the theory of human–computer interaction (HCI), this study addresses the consumer privacy concerns of IVAs, builds a model of the influence mechanism on consumer resistance, and then verifies the mediating effect of perceived creepiness and the moderating effect of anthropomorphized roles of IVAs and perceived CSR of IVAs companies. This research explores underlying mechanism with three experiments.

It turns out that consumers’ privacy concerns are related to their resistance to IVAs through perceived creepiness. The servant (vs. partner) anthropomorphized role of IVAs is likely to induce more privacy concerns and in turn higher resistance. At the same time, when the company’s CSR is perceived high, the impact of the concerns of IVAs’ privacy issues on consumer resistance will be weakened, and the intermediary mechanism of perceiving creepiness in HCI and anthropomorphism of new technology are further explained and verified. The differences between different age and gender are also revealed in the study.

The research conclusions have strategic reference significance for enterprises to build the design framework of IVAs and formulate the response strategy of IVAs’ privacy concerns. And it offers implications for researchers and closes the research gap of IVAs from the perspective of innovation resistance.

This paper analytically models and numerically investigates two operating levers, namely optimization of product price and optimization of product quality in the context of a manufacturer that sells the products directly in the marketplace. The study attempts to identify how optimizing product quality and product price can fulfill a manufacturer's economic aims such as maximization of the manufacturer's profit and market demand. Anchored to the extant literature, the demand is modeled as a parametric joint multiplicative function of price and quality. Further, price is modeled as a function of product quality.

First, the authors evolve the analytical expression for the manufacturer's profit. Thereafter, following the mathematical principles of unconstrained optimization, the authors arrive at the conditions for optimal product quality and product price. The authors further perform numerical experiments to understand the behavior of economic dimensions such as profit and demand with respect to sensitivities associated with cost, quality and price.

The authors find that under product quality optimization, the optimal product quality is a unique solution in that a highest possible theoretical manufacturer's profit is obtained. However, in the case of product price optimization, the optimal product price is non-unique and is a function of product quality. The authors further find that in the context of functional quality-level expectations, product quality optimization as an operating lever gives a better dividend. However, in the case of higher product quality expectations, product price optimization performs better than product quality optimization. Further, several novel findings are also obtained from numerical experimentations.

The findings of the authors' study have implications for types of industries characterized by relatively low as well as relatively high competitive intensity. Further, as opposed to several extant studies that have often carried out joint optimization of quality and price, the authors' study is one of the first to study the impact of product price and product quality on the manufacturer's economic objective in a disparate and focused manner, thus capturing individual effects.