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This paper explores the major factors influencing multinational companies’ (MNCs) propensity to change the level of resource commitments during financial crises in emerging markets. Favorable changes in the host government policies, market demand, firm strategy, and infrastructural conditions are hypothesized to influence the MNCs’ decision to increase resource commitments during a crisis. The hypotheses are tested with data collected in a survey of 82 MNCs during the recent Argentine financial crisis (late 2002). While all the above variables are considered by the respondents as generally important reasons for increasing resource commitments during a crisis, only favorable changes in government policies significantly influence MNCs’ decisions to change the level of resource commitments during the Argentine financial crisis. The research, managerial implications, and policy‐making implications are discussed.

Despite the importance of online word-of-mouth (WOM) communication to senders, receivers and concerned companies alike, a surprisingly limited amount of research exists on the impacts of online WOM participation on the senders themselves. Motivated by an attempt to fill this significant gap in the literature, this paper aims to investigate the sender outcomes of online WOM participation.

The authors draw on insights from focus group studies and psychological theories of emotions, catharsis and regret and the signaling theory to develop a conceptual model linking the drivers and content characteristics of online WOM participation and sender outcomes.

The findings show that sender outcomes from online WOM transmission differ by the types of drivers stimulating the online sharing activity and the level of exaggeration in the senders’ self-generated contents. Specifically, online WOM triggered by emotions leads to catharsis and emotional homeostasis among the senders, while that stimulated by motivational drivers such as altruism, reciprocity, self-enhancement and belongingness leads to sender happiness. Exaggeration in self-generated WOM contents by the senders, in turn, leads to delayed outcomes of sender regret and reduced sender trust in general online WOM contents.

The most important contribution to online WOM research lies in the study of the outcomes of WOM transmission from a sender’s point of view. By drawing on our exploratory findings and psychological theories of emotions, catharsis and regret and the signaling theory, the authors develop a conceptual model linking the drivers and the exaggeration nature of online WOM participation and sender outcomes.

Managers should realize that the most fundamental way of ensuring positive consumption experiences is to listen to customer voices, including even the most negative of feedback shared privately or publicly, and use that information to improve essential customer experience aspects. The finding on the effects of online WOM exaggerations on sender regret suggests that companies and consumers alike should work on ensuring producing more accurate and complete online customer reviews. The finding on the negative effect of online WOM exaggerations on sender trust raises an important question on the meaning of high quality reviews from the company’s perspective. To pursue high quality reviews, merchants should not only aim at receiving the highest possible numeric ratings but also encourage most truthful accounts of purchase and usage experiences. In turn, online platforms such as Amazon should also factor the quality of online ratings more effectively into their product recommendation algorithms.

In further consideration of consumer welfare implications, online WOM transmissions should be more recognized as a tool for allowing consumers to cleanse their emotions associated with marketing stimuli.

Overall, the qualitative study and proposed conceptual model contribute to a more thorough and deeper understanding of individual-level sender outcomes of online WOM participation.

The understanding of the motives for consumers’ support of business underdogs is generally limited. The purpose of this paper is to help address this important research topic by conceptualizing underdog affection as a theoretical construct capturing the emotional attachment held by some consumers toward underdog business entities and advances two perspectives (self- and other-oriented) to unravel its motivational underpinnings.

To test the conceptual model, a survey study was conducted involving 365 respondents drawn from an electronic alumni association list from a medium-sized Midwestern university in the USA. Exploratory factor analysis and confirmatory factor analyses were used to validate the scales, and the structural equations modeling method was used to test the hypothesized effects.

The data support most of the hypotheses (eight out of nine). Under the self-oriented perspective, commerce underdog affection is positively influenced by underdog orientation, need for uniqueness, nostalgia proneness, and hope, and is negatively impacted by their materialism level. Only hope did not impact consumer underdog affection. Under the other-oriented perspective, balance maintenance, top dog antipathy, and empathic concern positively influence underdog affection. The other-oriented factors, especially top dog antipathy and balance maintenance, show stronger effects on commerce underdog affection than self-oriented factors.

The sample was geographically restrictive in the sense that it measured only one group of respondents in the USA. The conceptual model is limited in terms of its coverage of the consequences of underdog affection. While discriminant validity is established in the scale development phase of the study, relatively close relationships do exist among some of these theoretical constructs.

Given the significant evidence linking consumers’ underdog affection to underdog support in commerce, small locally owned businesses could use underdog positioning advertising to differentiate themselves against national retailers. Due to their tendency to display higher underdog affection in commerce, people with higher levels of balance maintenance, top dog antipathy, underdog orientation, emphatic concern, and nostalgia proneness, and lower levels of materialism can be segmented for marketing purposes.

This research indicates that there are ways in which small business entities and non-profits alike can operate in a business setting that is increasingly more competitive and challenging for underdog entities.

This study integrates the various underdog studies across contexts to examine motives to underdog affection, a construct not yet operationalized in business studies. In addition, hypotheses linking eight specific antecedents to commerce underdog affection, via two theoretical perspectives, are empirically examined to assess relative as well as absolute effects.

The purpose of this paper is to seek an efficient method to tackle the energy provision problem for smart grid with sparse constraints and distributed energy and storage devices.

A complex smart grid is first studied, in which sparse constraints and the complex make-up of different energy consumption due to the integration of distributed energy and storage devices and the emergence of multisellers are discussed. Then, a real-time pricing scheme is formulated to tackle the demand response based on sparse bilevel programming. And then, a bilevel genetic algorithm (BGA) is further designed. Finally, simulations are conducted to evaluate the performance of the proposed approach.

The considered situation is widespread in practice, and meanwhile, the other cases including traditional model without the sparse constraints can be seen as its extensions. The BGA based on sparse bilevel programming has advantages of “no need of convexity of the model.” Moreover, it is feasible without the need to disclose the private information to others; therefore, privacies are protected and system scalability is kept. Simulation results validate the proposed approach has good performance in maximizing social welfare and balancing system energy distribution.

In this paper, the authors consider the sparse constraints due to the fact that each user can only choose limited utility companies per time slot. In reality, there exist some other sparse cases, which deserve further study in the future.

To the best of the authors’ knowledge, this is one of the very first studies to address pricing problems for the smart grid with consideration of sparse constraints and integration of distributed energy and storage devices.

This conceptual chapter aims to understand the role of artificial intelligence (AI) in value co-creation phenomena in a healthcare service ecosystem, through a literature review and the definition of a conceptual framework. AI, as an operant resource, can stimulate a completely patient-centered, adaptive and resilient healthcare system, and governance models in healthcare based on data-driven decision-making (DDDM), ensuring faster choices, more timely diagnosis and more personalized treatment paths. However, the full implementation of AI in healthcare is inhibited by some frictions, mainly related to the risk that the AI black box may generate an inadequate automatic decision, also due to the quality of data used, often partial and unstructured given the reluctance to share them by patients concerned by privacy threats. The co-design (multi-part and multi-level) of a predictive decision model based on the functional transparency of the AI algorithm would allow for augmented decision as result of an effective human–machine interaction. Healthcare actors could thus make decisions using the information detected by the software (based on clear cause-and-effect correlations and modifiable variables in case of mistakes), integrated with their professional knowledge. This would also help to strengthen the patient’s perception of the decision’s reliability and accuracy and the safety of the tool (factors that can affect his/her trust). AI may be considered as a driver for value co-creation in healthcare, thanks to transparency. It would allow the promotion of collaborative behaviors involving actors by generating new institutions and new resource integration practices among them.

This paper delves into the mechanism of the contingency framework for foreign entry mode decisions and identifies two essential tasks that jointly determine the outcome of the entry mode decision. It then recognizes a critical weakness in previous research pertaining to the comparison of entry modes along a key decision criterion, the degree of control. Existing studies generally treat equity involvement as the only source of entrant control, while largely ignoring non‐equity sources of control (i.e., bargaining power and trust). Non‐equity sources of control, when underutilized, amount to missed opportunities, increased resource commitments, and heightened risk exposures in foreign markets. Drawing from a pluralism perspective in transaction and relationship governance, the author presents a more integrative method for the ranking of entry modes along the degree of control. The central message is that companies entering foreign markets should make an earnest effort to identify trust and bargaining power situations and fully utilize their control potential in making entry mode decisions.

This paper aims to report the conductivity measurement of ten different surfactant-free microemulsions (SFMEs)

The variations of electrical conductivity as a function of water volume fraction are examined at one constant alcohol (or DMF, ethyl lactate, γ-valerolactone)/water, alcohol (or DMF, ethyl lactate, γ-valerolactone)/oil volume ratios for each sample.

Most of the results are consistent with percolation character. The conductive mechanism of these SFMEs is discussed by the percolation model, and it is found that it might be described with the static percolation model below the percolation threshold.

Our report gives a systematic research on the percolation mechanism of as many species of SFMEs as possible by the theoretical models

The purpose of this paper is to examine factors affecting consumers' acceptance of mobile marketing in China.

The authors draw on technology acceptance and uses and gratifications theories to develop a conceptual model of antecedent factors (including risk acceptance related to the mobile platform and personal attachment related to mobile devices) and marketing‐related and value‐based mobile activity related to the acceptance of mobile marketing practice. The conceptual model is tested using data collected among Chinese youth consumers.

The results confirm the importance of risk acceptance and personal attachment in influencing mobile marketing acceptance, and support the “priming” effect of regular mobile phone usage on orienting consumers toward accepting mobile marketing initiatives.

The study is limited to a specific sample of youth consumers in China. The findings illustrate the role of antecedent factors – including personal attachment and risk acceptance – related to acceptance of mobile marketing in the Chinese market and they emphasize the role of marketing‐related and value‐based mobile activity in mediating the relationships between antecedent factors and mobile marketing acceptance.

The findings illustrate the importance of recognizing the drivers of, and obstacles to, mobile marketing acceptance. These factors included the likelihood of providing information, likelihood of accessing content, likelihood of sharing content, level of risk acceptance, and level of personal attachment to one's mobile phone.

The paper adds to the growing literature on Chinese youth consumers by examining their acceptance of mobile marketing. The study reveals several implications for theory and practice relating to the antecedents of mobile marketing acceptance among the youth consumer segment within China, a large and emerging market.

This study aimed to develop a method to calculate the mattress indentation for further estimating spinal alignment.

A universal indentation calculation model is derived based on the system theory, and the deformation characteristics of each component are analyzed by the finite element (FE) model of a partial air-spring mattress under the initial air pressure of 0.01–0.025 MPa. Finally, the calculation error of the model is verified.

The results indicate that the indentation calculation model could describe the stain of a mattress given the load and the constitutive model of each element. In addition, the FE model of a partial air-spring mattress can be used for further simulation analysis with an error of 1.47–3.42 mm. Furthermore, the deformation of the series system is mainly contributed by the air spring and the components directly in contact with it, while the top component is mainly deflection deformation. In addition, the error of the calculation model is 2.17–5.59 mm on the condition of 0.01–0.025 MPa, satisfying the engineering application. Finally, the supine spinal alignment is successfully extracted from the mattress indentation.

The limitation of this study is that it needs to verify the practicality of the indentation calculation model for the Bonnier spiral spring mattress. The main feature of the Bonnier spring mattress is that all springs are connected, so the mattress deflection and neighborhood effect are more significant than those of the air-spring mattress. Therefore, the applicability of the model needs to be tested. Moreover, it is worth further research to reduce the deformation error of each component.

As part of the series of studies on the intelligent air-spring mattress, the indentation-based evaluation method of spinal alignment in sleep postures will be studied for hardness and intelligent regulation based on this study.

The results of this research are ultimately used for the intelligent adjustment of air-spring mattresses, which automatically adjusts the hardness according to the user's sleep postures and spinal alignment, thus maintaining optimal spinal biomechanics. The successful application of this result could improve the sleep health of the general public.

Based on the series system theory, an indentation calculation model for mattresses with arbitrary structure is proposed, overcoming the dependence of parameters on materials and their combinations when fitting the Burgers model. Further, the spinal alignment in supine posture is extracted from the indentation, laying a theoretical foundation for further recognition and adjustment of the spinal alignment of the intelligent mattress.

This study investigates occupational segregation, microaggression, and social exclusion as antecedents of social invisibility to predict employee intentions to leave. Furthermore, the authors question whether felt obligation moderates the relationship between social invisibility and intentions to leave. Finally, researchers explore various forms of occupational segregation, miscoaggression, and social exclusion from employee's perspective.

Two studies are conducted. Study 1 is quantitative where the data were collected from 273 nurses employed in various hospitals in Pakistan. Study 2 is qualitative where twelve confirmatory interviews were conducted to enrich our contextual understanding of the proposed relationships. The quantitative data are analyzed using partial least square methods via SmartPLS. The qualitative data analysis is based on a content analysis of interviews.

Surprisingly, occupational segregation does not predict social invisibility. Moreover, the relationship between occupational segregation and intentions to leave is not mediated via social invisibility. The issues such as social hierarchy and high power distance are reflected via the findings of the qualitative study.

The results provide insightful strategies to counter feelings of social invisibility among individuals performing those jobs which are considered stigmatized occupations.

This study uniquely presents three antecedents of social invisibility, its mediating role, and the moderation of felt obligation between social invisibility and intentions to leave.