Search results

Since research has already shown that social distance affects the relationship between employees and the organization, this study (1) examines job-related resources that contribute to teleworkers’ organizational commitment and (2) works out how internal communication professionals can strategically address them.

A total of 50 problem-centered, semi-structured qualitative interviews were conducted with teleworkers from Austrian and German organizations between March and June 2021.

The interview data resulted in eight job-related resources that contribute to teleworkers’ organizational commitment. By pointing out the communicative aspects of these resources, we discuss how internal communication professionals can strategically engage to maintain the connection between teleworkers and the organization despite the distance. It highlights the communicators’ role as a strategic communicators and networkers, as enabler and as key speaker for employees’ needs.

The data were collected during a health crisis (COVID-19 pandemic) in the context of Austrian and German organizations and refers to the perspective of employees for whom teleworking israther new.

The study provides in-depth insights into teleworkers’ expectations and entails clear implications for the practice of internal communication professionals to strengthen teleworkers’ commitment.

The traditional predictor of technical inefficiency proposed by Jondrow, Lovell, Materov, and Schmidt (1982) is a conditional expectation. This chapter explores whether, and by how much, the predictor can be improved by using auxiliary information in the conditioning set. It considers two types of stochastic frontier models. The first type is a panel data model where composed errors from past and future time periods contain information about contemporaneous technical inefficiency. The second type is when the stochastic frontier model is augmented by input ratio equations in which allocative inefficiency is correlated with technical inefficiency. Compared to the standard kernel-smoothing estimator, a newer estimator based on a local linear random forest helps mitigate the curse of dimensionality when the conditioning set is large. Besides numerous simulations, there is an illustrative empirical example.

Anyone who has recently watched television or movies can tell you that transgender, gender nonbinary or gender expansive people are becoming more visible in these media. This trend reflects the reality that younger generations are increasingly identifying with more fluid and nonbinary gender and sexual identities and are progressively expressing those identities in a more flexible and changing manner (Herman et al., 2022; Wilson & Meyer, 2021). Unsurprisingly then, those individuals are also more visible at work, including in workplaces with employer-mandated dress codes. Indeed, in 2020 the US Supreme Court decided a case involving a transgender woman, Aimee Stephens, who was fired because her employer, a funeral home, required her to conform to its gender-binary dress policy and wear clothing mandatory for people assigned male at birth, rather than appropriate for her female gender identity ( Bostock v. Clayton County, 2020).

However, as the description of Aimee Stephens's own experience illustrates, often these employer appearance codes are based on a binary and fixed conception of gender and gender identity and expression at odds with the increasing number of workers who do not identify within those rigid parameters. Moreover, even when an employee, like Aimee Stephens herself, could have fit within her employer's dress code, the improper application of that policy to her, or employer concerns about customer or co-worker discomfort with an employee's appearance under the policy may mean that a worker's identity and expression may still conflict with a workplace appearance code. For gender nonbinary or nonconforming individuals, these complications are magnified.

This chapter explores the practical problems and barriers that employer dress codes have on employees whose gender identity and/or presentation move beyond the traditional male/female binary. Using insights from queer theory, gender expansive employees serve to interrogate fundamental assumptions behind workplace dress policies and the formal and informal ways in which these policies are policed. The chapter will explore that discordance, examine possible employer resolutions, and evaluate the strengths and weaknesses of those responses.

Focusing on micro-level indicators, we investigate financial inclusion levels in rural China, examining its determinants and impact on household welfare. We construct a financial inclusion index of four essential financial services: savings, digital payments, credit and insurance. We identify factors influencing financial inclusion among Chinese rural households and assess the effects of financial inclusion on household welfare.

With the entropy method, we use data from the 2019 China Household Finance Survey to assess financial inclusion levels in rural China. Determinants and their impact on welfare are analyzed through probit and ordinary least squares models, respectively. Propensity scoring matching is applied to address potential endogeneity.

We reveal that rural households exhibit limited usage of formal financial services, with notable regional disparities. The eastern region enjoys the highest financial inclusion and the central region lags behind. Household characteristics such as family size, education level of the household head, income, employment status and financial literacy significantly influence financial inclusion. Financial inclusion positively impacts household welfare as indicated by household consumption expenditure. The use of different types of financial services is crucial with varying but significant effects on household welfare.

This study offers valuable insights into China’s rural financial inclusion progress, highlighting potential barriers and guiding government actions.

Homelessness has many causes and also is stigmatized in the United States, leading to much misunderstanding of its causes and what policy solutions may ameliorate the problem. The problem is of course getting worse and impacting many communities far removed from the West Coast cities the authors examine in this study. This analysis examines the socioeconomic variables influencing homelessness on the West Coast in recent years. The authors utilize a panel fixed effects model that explicitly includes measures of healthcare access and availability to account for the additional health risks faced by individuals who lack shelter. The authors estimate a spatial error model (SEM) in order to better understand the impacts that systemic shocks, such as the COVID-19 pandemic, have on a variety of factors that directly influence productivity and other measures of welfare such as income inequality, housing supply, healthcare investment, and homelessness.

This paper aims to investigate the interrelated role of relational commitment and dependence as drivers of key performance outcomes. Specifically, the authors provide a conceptual model of the impact of commitment on relationship value dependence and switching cost dependence. The authors further investigate how these dimensions of dependence offer differing noneconomic and economic paths to strategic and financial performance.

Survey data was collected from 296 purchasing agents across multiple industries located in the USA. The conceptual model and accompanying hypotheses were tested via partial least squares structural equation modeling.

The results show that the relational path is driven by affective and normative commitment, which are related to relationship value dependence. Conversely, calculative commitment is related to switching cost dependence. This economic path is related to both strategic and financial performance, whereas the relational path is more closely related to strategic as opposed to financial performance outcomes.

This study extends research on Business-To-Business (B2B) relationships by leveraging social exchange theory to examine the interrelated roles played by two forms of dependence on performance outcomes. Thus, the authors answer Scheer et al.’s (2015) call for research into the two distinct types of dependence – relationship value and switching cost dependence – and their roles in determining B2B relationship outcomes. The findings contribute to the literature by integrating social exchange and relationship marketing concepts to develop a dual pathway approach to B2B partnerships.

The results suggest that dependence is not necessarily negative for firms. Specifically, buyers can and do still exhibit positive performance, both strategic and financial, in relationships with suppliers even when dependent on the relationship. Regardless of whether buyers are dependent due to a relationship or economic factors, both can, in different ways, lead to positive strategic and financial outcomes. Together, the authors contribute to the understanding of B2B partnerships by offering guidelines for both buyers and suppliers in the dyad.

The authors derive a comprehensive model depicting primarily relational and economic paths to performance through different types of commitment and dependence. The authors contribute to the literature by demonstrating that relational and economic paths to success are not the same, highlighting how firms could influence performance even when the relationship is not necessarily characterized by generally positive relational benefits and behaviors.

Four reputed leaders for the coming years in the field of special education for individuals with emotional and behavioral disorders (EBD) each with a slightly different perspective on the field were asked to respond independently to a prompt asking what does special education mean for students with EBD and what is being done and how do we maintain tradition? The contributors' responses to the prompt are presented and then summarized across the essays. A remarkable consistency emerges across the independent essays. In addition to the tradition of providing a free and appropriate education in the least restrictive environment, the contributors identify needs to support teachers serving this population. Needs in teacher training and the expertise required to meet the needs of individuals with EBD are outlined as well as potential contributions of technology to carry out specific tasks. We conclude with a call for increased advocacy for use of the knowledge that we currently possess and that which will soon be discovered to support students with EBD as well as their teachers. We also note that the contributors' names are listed alphabetically to acknowledge the equality of each person to the final product.

We operate in a complex dynamic world where human activities interfere with the environment in ways that may cause unpredictable extreme outcomes that reflect exposure to uncertainty and unknown factors as opposed to identifiable risk events. As humans, we tend to downplay the effects of uncertainty and create a false sense of security by adopting formal control-based management practices where we in truth face more uncertainties than we realize. Hence, we attempt to assess extreme disaster events to mitigate adverse effects but fail to address the underlying causes for the exposures rooted in the way we have organized global economic activities. Exposures partially derive from the way enterprises govern their economic assets while systemic exposures derive from the way we conduct our global business practices. Identified exposures are typically local whereas the systemic causes are global with collective societal effects. Therefore, mitigating enterprise exposures will not address the global systemic causes for the extreme societal effects. To reach more sustainable solutions we must involve businesses that operate the global economy as well as the societies they operate in around the world. Given the extreme uncertainty of systemic risks, grand solutions cannot be derived from computational analytics but require experimentation among engaged public and private organizations and open collaborative learning to identify viable solutions from diverse insights. We must embrace uncertainty to explore innovative opportunities for proposed solutions and implement them in gradual co-evolving progression to develop viable sustainable economic outcomes.

Resilience while learning is the capacity to initiate, persist and direct effort toward learning when experiencing unpleasant affective states. The underlying mechanisms of resilience are emotional buffering and self-regulation when experiencing unpleasant affective states. The authors identified four factors that support resilience while learning: positive emotional engagement, creative problem-solving, learning identity and social support. The authors developed and tested scales and found evidence to support the four-factor model of resilience. The authors offer a person-centered approach to resilience in learning by conducting a latent profile analysis that tested the likelihood of resilience based on profiles of differences in scores on these factors under two affective conditions: (unpleasant) learning during frustration versus (pleasant) learning during progress. A quarter of individuals activated the four resilience factors in pleasant and unpleasant affective states, while 75% of participants saw decrements in these factors when faced with frustration. The results support a four-factor, person-centered approach to resilience while learning.

The authors develop and test a four-factor model of resilience and test the model in a group of 330 management undergraduate and graduate students. Each participant identified two learning episodes in their responses, one while frustrated and one while making progress, and ranked the level of intensity on the four resilience factors. Analysis on an additional 88 subjects provided additional support for the validation and reliability of scales.

Results revealed 2 latent profiles groups, with 25% of the sample associated with resilience (low difference on resilience factors between the two learning episodes) and 75% who remain susceptible to unpleasant emotions (high difference between the two learning episodes).

The study supports a person-centered approach to resilience while learning (in contrast to a variable centered approach).

The study provides a means to classify individuals using a person-centered, rather than a variable-centered approach. An understanding of how individuals buffer and self-regulate while experiencing unpleasant affect while learning can help educators, consultants and managers develop better interventions for learning.

This study addresses the growing concern over student success associated with increased dropout rates among undergraduate business students, and the failure of many management developments and executive training efforts. This study suggests that looking at specific variables may not provide insight into the complex relationship between learning outcomes and factors that support resilience in learning.

There is growing interest in understanding resilience factors from a person-centered perspective using analytical methods such as latent profile analysis. This is the first study to look at how individuals can be grouped into similar profiles based on four resilience factors.