Search results

The aim of this research is to determine the extent to which the human resource (HR) function can screen and potentially predict suicidal employees and offer preventative mental health assistance.

Drawing from the 2019 National Survey of Drug Use and Health (N = 56,136), this paper employs multivariate binary logistic regression to model the work-related predictors of suicidal ideation, planning and attempts.

The results indicate that known periods of joblessness, the total number of sick days and absenteeism over the last 12 months are significantly associated with various suicidal outcomes while controlling for key psychosocial correlates. The results also indicate that employee assistance programs are associated with a significantly reduced likelihood of suicidal ideation. These findings are consistent with conservation of resources theory.

This research demonstrates preliminarily that the HR function can unobtrusively detect employee mental health crises by collecting data on key predictors.

In the era of COVID-19, employers have a duty of care to safeguard employee mental health. To this end, the authors offer an innovative way through which the HR function can employ predictive analytics to address mental health crises before they result in tragedy.

This study aims to examine the applicability of Hartmann et al.’s (2018) service ecosystem framework to the day-to-day management of the modern sales force. The authors provide a review of the framework, acknowledging its strengths, while also indicating areas for advancement. The authors conclude with recommendations to the framework and indicate opportunities where future research could advance sales theory.

A review of the theoretical underpinnings of the service ecosystem framework is weighed against the established roles and responsibilities of the modern sales force in the literature.

The ability of the framework to capture the multi-level, multi-actor and dynamic aspects of sales represents an improvement in the conceptualization of selling is critical. Suggestions around the refinement for meso-level sales interactions and a more pliant application of service dominant-logic are offered.

The suggested extensions of the framework continue the advancement of novel theorization for the field of sales. Priorities for future research include consideration of ethical implications of the framework and formulations of new management strategies reflective of the broad and dynamic properties of the ecosystem conceptualization.

This paper provides managerial guidelines and implications tied specifically to the thick and thin crossing points and how they may impact employee decision-making.

To the best of the authors’ knowledge, this study is the first to pointedly examine the service ecosystem framework with respect to established principles of managing a modern sales force.

Some individuals with autism may engage in violent behaviour. Research into autism specific factors (ASFs) that may contribute to violence is limited. The purpose of this paper is to explore the feasibility of use of an ASF framework which was developed to inform risk formulation and treatment needs.

Retrospective identification and evaluation of ASFs in offenders with autism (N = 13) at childhood, time of index offence and in current risk behaviours. The ASFs described in the framework were repetitive behaviours and circumscribed interests; poor social understanding and empathy; sensitivity to sensory stimulation; and disruption to rigid behavioural routines or difficulties coping with change.

There was evidence for all four ASFs being consistently present in childhood, contributing to violent behaviour at the index offence and current risk behaviours in at least one case. Poor social understanding and empathy was often present at both childhood and index offence in all cases. Of the seven cases with offence paralleling behaviour, five had at least one ASF present at each timepoint.

This proof-of-concept study provides initial support that ASFs play a role in offending behaviour of individuals with autism. Clinicians working in specialist and generic forensic services, with an in-depth knowledge of autism, could use the ASF framework to enhance risk assessments and facilitate more targeted treatment planning for offenders with autism in specialist and general forensic services.

To the best of the authors’ knowledge, this study is the first to test the application of the ASF framework in an autistic offending population.

The main purpose of this research is to investigate factors influencing rural women entrepreneurship development and sustainable rural livelihoods in Manicaland province of Zimbabwe.

A quantitative research was conducted in Manicaland province in Zimbabwe. Data were collected through structured questionnaires from 400 women entrepreneurs in various sectors. The participants were in vegetable vending, operating clothing flea markets and cross border trading. A self-administered structured questionnaire was used to collect data from respondents. Structural equation modeling in SmartPLS version 3 was used to test the research hypotheses.

The study established that women entrepreneurship is driven by financial factors, positive environmental factors, positive psychological factors as well as positive sociological factors for a sustainable rural livelihood.

It is clear that if the discovered challenges are not addressed, sustainability of women entrepreneurship will remain a dream.

The study came up with strategies for improving women entrepreneurship activities. Future research can be done in other areas of provinces to avoid generalization challenges.

Many challenges hinder the sustainability of women entrepreneurship. Major impediments to women entrepreneurship comprises inadequate support from government schemes, patriarchal societal structure of the community, lack of relevant entrepreneurial knowledge to manage businesses, lack of collateral security to access funding, time limitation or role conflict to balance family pressures and business.

The study recommends proper entrepreneurship education and training, supportive government schemes and access to network affiliation/connection to sustain women entrepreneurship.

The purpose of this study is to frame digital transformation (DT) within municipalities to improve the life cycles of urban infrastructure.

The study provides the results from a systematic review of the literature on concepts of DT and its implications for municipalities, barriers and challenges to DT, as well existing DT frameworks for municipalities and their built assets. This literature review leads to the development of a DT framework to help cities conduct a planned and federated DT beforehand. Then, workshops are conducted with two major Canadian municipalities.

The results of these studies point to the need for a dedicated DT framework for municipalities because of their particular context and their role and proximity to citizens. The theoretical framework develops 22 elements, which are divided among 6 categories. Through its application, the framework helps to identify and target the predominant issues hindering the DT of municipalities, specifically “legacy practices” and “data management.”

Limitations include limited experimental conditions and small sample size. Further work is needed to validate the framework. Other approaches are advocated to complement the data collection and analysis to generate more convincing results.

The theoretical framework was validated through two case studies on two large Canadian municipalities.

Municipalities maximize the value they provide to citizens and to be at the forefront of resilience and sustainability concerns. The use of technology, digital processes and initiatives helps cities to improve planning, optimize works and provide better services to citizens.

The framework is original in that it specifically aligns assets management with DT in a municipal context.

This paper aims to examine the internal logical relationship between two intergenerational inheritance ways of passing property rights and residual control rights (RCR) and to construct a conceptual model comprising transfer elements, paths and timing of succession in this process.

Driven by the cases of Haixin, Tianyijiao and Changhe Group, this paper applies research methods of copying and expanding analysis logic, progressive deduction, content analysis and comparative research based on the perspective of HeXie theory to explore the deep interrelation of transfer elements, paths and timing during family business succession.

The findings present that the content of intergenerational inheritance of a family firm is the inheritance of property rights and RCR. First, the inheritance of property rights is a static inheritance of time-point delivery, whereas the inheritance of RCR is a dynamic inheritance process for a period of time. Second, the inheritance of property rights and RCR are not independent; only a “HeXie” succession of both rights can realize a successful inheritance of family firms.

This paper constructs the paths and timing model of intergenerational inheritance of property rights and RCR in family firms. This paper integrates the current literature studies on the family inheritance of property rights and RCR and explains their internal mechanisms. This paper also provides a theoretical foundation and empirical evidence for family business transitions in the business world.

This study uses the resource-based view (RBV) and isomorphism to investigate the influence of data-based resources (i.e. bigness of data, data accessibility (DA) and data completeness (DC)) on big data analytics (BDA) use under the moderation effect of organizational culture (i.e. IT proactive climate). It also analyzes the possible relationship between BDA implementation and value creation.

The empirical validation of the research model was performed through a cross-sectional procedure to gather survey-based responses. The data obtained from a sample of 190 IT executives having relevant educational backgrounds and experienced in the field of big data and business analytics were analyzed using structural equation modeling.

BDA usage can generate significant value if supported by proper levels of DA and DC, which are benefits obtained from the bigness of data (high volume, variety and velocity of data). In addition, data-driven benefits have stronger impacts on BDA usage in firms with higher levels of IT proactive climate.

The present paper has extended the existing literature as it demonstrates facilitating characteristic of data-based resources (i.e. DA and DC) on BDA implementation which can be intensified with an established IT proactive climate in the firm. Additionally, it provides further theoretical and practical insights which are illustrated ahead.

With access to the large-scale search data from Rightmove plc, the paper firstly indicated the possibility of using user-generated data from online property portals to predict housing market activities and secondly embraced a GIS approach to explore what people search for housing and what they chose and investigated the issue of mismatch between search patterns and revealed patterns. Based on the analysis, the paper contributes a visual GIS-based approach which may help planners and designers to make more informed decisions related to new housing supply, particularly where to build, what to build and how many to build.

The paper used the 2013 housing search data from Rightmove and the 2013 price data from Land Registry with transactions made after the search period and embraced a GIS approach to explore the potential housing demand patterns and the mismatch between searches and sales. In the analysis, the paper employed the K-means approach to group prices into five levels and used GIS software to draw maps based on these price levels. The paper also employed a simple analysis of linear regression based on the coefficient of determination to investigate the relationship between online property views and values of house sales.

The result indicated the strong relationship between online property views and the values of house sales, implying the possibility of using search data from online property portals to predict housing market activities. It then explore the spatial housing demand patterns based on searches and showed a mismatch between the spatial patterns of housing search and actual moves across submarkets. The findings may not be very surprising but the main objective of the paper is to open up a potentially useful methodological approach which could be extended in future research.

It is important to identify search patterns from people who search with the intention to buy houses and from people who search with no intention to purchase properties. Rightmove data do not adequately represent housing search activity, and therefore more attention should be paid to this issue. The analysis of housing search helps us have a better understanding of households' preferences to better estimate housing demand and develop search-based prediction models. It also helps us identify spatial and structural submarkets and examine the mismatches between current housing stock and housing demand in submarkets.

The GIS approach in this paper may help planners and designers better allocate land resources for new housing supply based on households' spatial and structural preferences by identifying high and low demand areas with high searches relative to low housing stocks. Furthermore, the analysis of housing search patterns helps identify areas with latent demand, and when combined with the analysis of transaction patterns, it is possible to realise the areas with a lack of housing supply relative to excess demand or a lack of latent demand relative to the housing stock.

The paper proves the usefulness of a GIS approach to investigate households' preferences and aspirations through search data from online property portals. The contribution of the paper is the visual GIS-based approach, and based on this approach the paper fills the international knowledge gap in exploring effective approaches to analysing user-generated search data and market outcome data in combination.