Search results

This paper aims to apply a mixed-methods approach to redefine essential work skill sets, propose components of these skill sets that are necessary for workers in the contexts of emerging market economies (EMEs), examine potential selection tools that should be applied across firms and explain implications for the labour process theory (LPT) of work.

During the first phase of this study, qualitative data was collected from methods, including semi-structured interviews with human resources (HR) experts from the Personnel Management Association of Thailand, top and HR executives and managers of firms across industries in Thailand. Non-participant observations were made during the pre-interview, interview and post-interview stages. Analysis of archival documents and Web-based resources was then conducted. The authors used the qualitative data obtained from the first phase to develop survey instruments for conducting quantitative research during the second phase of this study.

The empirical findings demonstrate that essential work skill sets are “soft skills” that help workers survive and thrive in the business arena in EMEs. These essential work skill sets have implications for the LPT of work in that they play an important role in transferring the power of negotiation from employers to workers in the labour market. Essential work skill sets here can be divided into eight skill domains: (1) ideation and system thinking, (2) information and digital literacy, (3) social skills with appreciation for diversity and inclusion, (4) communication and language, (5) creativity and innovation, (6) emotional quotient (EQ) for self-management and development, (7) growth/outward mindset and (8) cognitive skills for the job role. Within each essential work skill set, there are several skills that workers in the current world of work need to possess (42 skills in total). Additionally, potential selection tools include behavioural observation, behavioural-based interviews, STAR (Situation, Task, Action and Results) interviews, role plays, case studies and simulations, high-pressure interview questions, project assignments, assessment centres, in-depth interview questions and special methods, such as face reading and fingerprint reading. Top and HR managers across industries strongly agree that the eight essential work skill sets and 42 skills are necessary for workers to survive in the business arena in EMEs. They also strongly agree that talent selection tools, especially behavioural-based interviews, are used by their firms to select high-skilled job candidates in the labour market.

Because the eight essential skill sets proposed in this paper are based primarily on the qualitative data obtained from top/HR managers in firms across some industries, generalization to respondents across other industries or across other EMEs may be limited. It is possible that the context of other EMEs may be different from that of Thailand. In this regard, some of the essential work skill sets that are suitable in the case of Thailand may not be suitable in the case of other EMEs. Future studies should thus explore how institutional contexts of other countries/economies shape the definition of essential skill sets and their components, as well as potential selection tools that shall be applied to select high-skilled labour in those contexts.

This paper provides practical implications for top managers and/or HR managers of firms across various industries in EMEs. In particular, managers should internally train and develop their employees/workers to possess the eight essential skill sets: (1) ideation and system thinking, (2) information and digital literacy, (3) social skills with appreciation for diversity and inclusion, (4) communication and language, (5) creativity and innovation, (6) EQ for self-management and development, (7) growth/outward mindset and (8) cognitive skills for the specific job role so that their employees/workers can survive and thrive in the era of the brittleness, anxiety, non-linearity and incomprehensibility of the business world under pandemic conditions. Additionally, top managers and/or HR managers of these firms should apply the potential selection tools proposed in this paper to probe into job candidates’ past experience and behaviours to better predict such candidates’ success at work. In this regard, job candidates/workers should prepare themselves to possess these essential work skill sets so that they can be successful in the business arena and should understand potential selection tools that firms may apply to recruit and select them.

This paper provides social/policy implications for the government and/or relevant public agencies of Thailand and of other EMEs. These governments should encourage firms across industries to invest resources in training and developing their employees/workers to possess those essential work skill sets so that these employees/workers are industry-ready, leading to the alleviation of the problems of skill and mismatch in the labour market.

This paper contributes to the prior literature on human resource management (HRM), the comparative institutional perspective on employment systems based on the varieties of capitalism (VoC) framework and the LPT of work in the following ways: first, this paper fills in the research gap in the field of HRM that calls for studies that explore how the COVID-19 pandemic shapes essential skill sets and skills development among workers within firms (Cooke et al., 2021). Second, this paper provides implications for the LPT of work regarding how essential work skill sets are likely to return the power of negotiation from employers to workers in EMEs during the current situation. Third, the VoC framework tends to focus on only two types of economies, liberal market economies and coordinated market economies. However, this paper examines essential work skill sets and potential screening tools in the context of the underresearched country of Thailand, an EME. In fact, the Thai labour market is quite different from that of other EMEs labour markets, as it is impacted by an aging workforce. This paper contributes to the literature on comparative institutional perspectives on employment systems as it redefines essential work skill sets, proposes various components of these skill sets among workers and examines potential selection tools that are applied across firms located in EMEs.

Asynchronous video interviews (AVIs) enable recruiters and job candidates to conduct and review employment interviews at different points in time, promising improved cost and time efficiencies for all users. This research aims to investigate the implementation and normalization process of AVI in the hospitality industry with the unified theory of acceptance and use of technology (UTAUT) and the normalization process theory (NPT) providing theoretical support.

Semi-structured interviews have been conducted with hiring managers from three different hospitality companies, which were in different stages of the implementation process. The data have been recorded, transcribed and coded according to the UTAUT and NPT constructs, revealing emergent themes.

Five overarching themes emerged: AVI effort and efficiency expectation; augmentation to the interview process; challenges for the applicant; challenges for the recruiter; and issues with applicant interviewing aesthetics. Additional coding and analysis with NPT identified the following in terms of evaluation of the implementation process: participants’ implementation activities showed a tendency to emanate from cognitive participation (relationship work), leading to coherence (sense-making work), followed by collective action (enactment of work/operational work) and finally reflexive monitoring (appraisal work).

Findings from this research include recommendations for the best practices integrating AVI into the hospitality employee selection process.

Given the increased demands on the recruitment and selection of talent in the hospitality industry, several organizations have turned to mechanized HR software platforms. The impact of interview modalities and particularly AVI has received limited research attention, thus this study expanded this new stream of literature. Furthermore, this research is among a nascent stream using NPT to evaluate the implementation and normalization of this new technology.

Asynchronous Video Interviews (AVIs) incorporating Artificial Intelligence (AI)-assisted assessment has become popular as a pre-employment screening method. The extent to which applicants engage in deceptive impression management (IM) behaviors during these interviews remains uncertain. Furthermore, the accuracy of human detection in identifying such deceptive IM behaviors is limited. This study seeks to explore differences in deceptive IM behaviors by applicants across video interview modes (AVIs vs Synchronous Video Interviews (SVIs)) and the use of AI-assisted assessment (AI vs non-AI). The study also investigates if video interview modes affect human interviewers' ability to detect deceptive IM behaviors.

The authors conducted a field study with four conditions based on two critical factors: the synchrony of video interviews (AVI vs SVI) and the presence of AI-assisted assessment (AI vs Non-AI): Non-AI-assisted AVIs, AI-assisted AVIs, Non-AI-assisted SVIs and AI-assisted SVIs. The study involved 144 pairs of interviewees and interviewers/assessors. To assess applicants' deceptive IM behaviors, the authors employed a combination of interviewee self-reports and interviewer perceptions.

The results indicate that AVIs elicited fewer instances of deceptive IM behaviors across all dimensions when compared to SVIs. Furthermore, using AI-assisted assessment in both video interview modes resulted in less extensive image creation than non-AI settings. However, the study revealed that human interviewers had difficulties detecting deceptive IM behaviors regardless of the mode used, except for extensive faking in AVIs.

The study is the first to address the call for research on the impact of video interview modes and AI on interviewee faking and interviewer accuracy. This research enhances the authors’ understanding of the practical implications associated with the use of different video interview modes and AI algorithms in the pre-employment screening process. The study contributes to the existing literature by refining the theoretical model of faking likelihood in employment interviews according to media richness theory and the model of volitional rating behavior based on expectancy theory in the context of AVIs and AI-assisted assessment.

Organization development is focused on implementing a planned process of positive humanistic change in organizations through the use of social science theory, action research, and data-based feedback methods. The role of personality in that change process, however, has historically been ignored or relegated to a limited set of interventions. The purpose of this chapter is to provide a conceptual overview of the linkages between personality and OD, discuss the current state of personality in the field including key trends in talent management, and offer a new multi-level framework for conceptualizing applications of personality for different types of OD efforts. The chapter concludes with implications for research and practice.

The purpose of this paper is to examine employers’ use of social networking sites (SNSs) within employee selection.

In-depth interviews were conducted with 15 organisations to gain an understanding of how they accessed, observed and utilised data from SNSs in their selection procedures, as well as gaining an insight into employers’ perceptions of candidate privacy and discrimination.

SNS profiles were either accessed as part of an organisation’s official selection process, through integrating internet screening as part of the formal process and obtaining candidate permission, or through covert (without consent) observation. Facebook was primarily used to identify a candidate’s organisation fit and make assessment of their soft skills, whereas LinkedIn distinguished their professional attributes and their job fit. Problems were associated with the extent to which SNSs were reflective of the person and whether a candidate’s personal life reflected their work persona. Respondents focused more upon the legality, rather than the ethics, of accessing “private” information via SNSs.

Further research is needed to consider the content and predictive validity of SNSs as a selection tool before their utility can be ascertained.

Organisations should have a clear goal when utilising SNSs, be aware of the value of the information and consider how it complements other selection tools. Selectors should have integrity throughout the selection process, view SNSs as a support tool and use their common sense.

The in-depth nature of this research enabled the authors to understand how and why organisations are currently utilising SNSs within selection.

Presents a model of the machining system selection process that is focused on capital intensive, complex machining systems that are intended to provide service over a long time horizon. This model was developed based on interviews with both machine tool suppliers and buyers. The systems considered here increasingly face potentially conflicting demands such as: the ability to be quickly and inexpensively upgraded and reconfigured in order to have quick new product change‐over and ramp‐up time; and high product variety at close to mass production costs. This new “reconfigurability” capability increases the importance of the supplier‐buyer relationship after the machining system has been selected. We also remark that the selection process can serve as the basis for internal consensus and team building within the buyer firm and for enhancing supplier base quality.

Additive manufacturing (AM) can reduce the process supply chain and encourage manufacturing innovation in remote or austere environments by producing an array of replacement/spare parts from a single raw material source. The wide variety of AM technologies, materials, and potential use cases necessitates decision support that addresses the diverse considerations of deployable manufacturing. The paper aims to discuss these issues.

Semi-structured interviews with potential users are conducted in order to establish a general deployable AM framework. This framework then forms the basis for a decision support tool to help users determine appropriate machines and materials for their desired deployable context.

User constraints are separated into process, machine, part, material, environmental, and logistical categories to form a deployable AM framework. These inform a “tiered funnel” selection tool, where each stage requires increased user knowledge of AM and the deployable context. The tool can help users narrow a database of candidate machines and materials to those appropriate for their deployable context.

Future work will focus on expanding the environments covered by the decision support tool and expanding the user needs pool to incorporate private sector users and users less familiar with AM processes.

The framework in this paper can influence the growth of existing deployable manufacturing endeavors (e.g. Rapid Equipping Force Expeditionary Lab – Mobile, Army’s Mobile Parts Hospital, etc.) and considerations for future deployable AM systems.

This work represents novel research to develop both a framework for deployable AM and a user-driven decision support tool to select a process and material for the deployable context.

Traditional market selection analysis relies on purely macroeconomic and political factors and fails to account for an emerging market's dynamism and future potential. The objective of this paper is to present a tool composed of four criteria specific to the preliminary assessment of emerging markets (EM) as international expansion opportunities.

Based on the literature pointing out the limitations of international market selection (IMS) models and the need for a specialized approach, additional criteria are introduced to assess emerging market potential. Review of prior work on internationalization, EM and market selection provided the rationale for the selected criteria. Using secondary data and primary data from a sample of 500, the proposed criteria are applied to the assessment of an emerging market for US apparel specialty retailers.

Assessment of the emerging market with the criteria introduced revealed growth and sourcing opportunities that might otherwise have been overlooked. Case application exposed strong future market potential, manageable level of cultural distance, supportive and developing local industry and positive customer receptiveness for foreign products and business. The findings illustrate the need to improve and supplement assessment criteria of traditional analysis for EM.

Follow‐up studies validating, integrating and determining the relative importance of the criteria introduced will contribute to the development of an assessment model for EM.

A useful complementary tool for international marketers.

The paper develops the body of knowledge on IMS by addressing the shortcomings of traditional analysis and expands the two prior studies on emerging market potential.

The purpose of the paper is to provide a conceptual foundation to enhance the body of knowledge related to supplier selection in light of global supply chain disruptions and risk.

The proposed tool is based on a multi‐criteria optimization framework, which will enable the user to gain a better understanding of how the consideration of each of these risk measures will affect the recommended solution/supply base. The model serves as a complement to existing supplier selection models by incorporating regional risks associated with potential suppliers' locations and density risks based on great circle distance measures.

The paper demonstrated the proposed model by using the great circle distance measure to calculate the density risk and two secondary data sources to capture environmental risk. One measure captures a variety of environmental issues such as political, legal, security, fiscal, labor, and regulatory issues. The other measure captures the historical effects of weather on dollar and human losses in each country of the world, which represents the potential for severe weather events and the country's ability to react to these events.

Although the paper does not consider all possible risks, it augments prior research through the development of a decision support tool that offers supply risk mitigation when sourcing globally. Specifically, the tool allows for the analysis and mitigation of two key global risk measures, environmental risk and density risk, when selecting suppliers for mission‐critical parts. The model is able to support various sourcing strategies such as sole, multiple and cross sourcing and can be used in conjunction with other disruption mitigation strategies such as supply redundancy.

Global sourcing has provided significant performance enhancements, but has put firms in a vulnerable position relative to the potential devastating effects of supply disruptions. While supply managers are cognizant of the risks associated with global sourcing, limited knowledge and tools are available to allow them to mitigate these risks. Although it would need to be adapted to the nuances of company supply chains, it is believed that the tool provides value to managerial decision making relative to the sourcing of mission critical parts/products.

Prior work in this area has not adequately incorporated contemporary issues and risks in global sourcing. The paper augments prior research through the development of a multi‐objective decision support model for strategic supplier selection that is focused on two important contemporary factors: environmental risk and density risk. The proposed model captures important interdependent relationships between these two factors that have not been considered in prior selection models.