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The purpose of this study was to investigate the roles of employee experience and top management commitment in the relationship between human resource (HR) records management culture and HR records privacy control in organisations in Ghana.

Structural equation modelling was used in analysing the data. Following the specification of the model, three main types of analyses were carried out. They were reflective measurement model analyses to test reliability and validity; formative measurement model analyses to test redundancy, collinearity, significance and relevance of the lower-order constructs; and structural model analyses to ascertain the explanatory and predictive powers of the model, significance of the hypotheses and their effect sizes.

The study confirmed that communication, privacy awareness and training and risk assessment are dimensions of HR records management culture. Concerning the hypotheses, it was established that HR records management culture is related to HR records privacy control. Also, the study showed that employee experience positively moderated the relationship HR records management culture has with HR records privacy control. However, top management commitment negatively moderated the relationship HR records management culture has with HR records privacy control.

Organisations committed to the privacy control of HR records need to ensure the retention of their employees, as the longer they stay with the organisation, the more they embody the HR records management culture which improves the privacy control of HR records. For top management commitment, it should be restricted to providing strategic direction for HR records privacy control, as the day-to-day influence of top management commitment on the HR records management culture does not improve the privacy control of HR records.

This study demonstrates that communication, privacy awareness and training and risk assessment are dimensions of HR record management culture. Also, the extent of employee experience and top management commitment required in the relationship between HR records management culture and HR records privacy control is revealed.

Research serves to elucidate and tackle real-world issues (e.g. capitalizing opportunities and solving problems). Critical to research is the concept of validity, which gauges the extent to which research is adequate and appropriate in representing what it intends to measure and test. In this vein, this article aims to present a typology of validity to aid researchers in this endeavor.

Employing a synthesis approach informed by the 3Es of expertise, experience, and exposure, this article maintains a sharp focus on delineating the concept of validity and presenting its typology.

This article emphasizes the importance of validity and explains how and when different types of validity can be established. First and foremost, content validity and face validity are prerequisites assessed before data collection, whereas convergent validity and discriminant validity come into play during the evaluation of the measurement model post-data collection, while nomological validity and predictive validity are crucial in the evaluation of the structural model following the evaluation of the measurement model. Additionally, content, face, convergent and discriminant validity contribute to construct validity as they pertain to concept(s), while nomological and predictive validity contribute to criterion validity as they relate to relationship(s). Last but not least, content and face validity are established by humans, thereby contributing to the assessment of substantive significance, whereas convergent, discriminant, nomological and predictive validity are established by statistics, thereby contributing to the assessment of statistical significance.

This article contributes to a deeper understanding of validity’s multifaceted nature in research, providing a practical guide for its application across various research stages.

The study explored various dimensions of overconfidence bias (OB) among retail investors in Indian financial markets. Further, these dimensions were validated through formative assessments for OB.

The study applied exploratory factor analysis (EFA) to 764 respondents to explore dimensions of OB. These were validated with formative assessments on 489 respondents by the partial least square path modeling (PLS-PM) approach in SmartPLS 4.0 software.

The major findings of EFA explored four dimensions for OB, i.e. accuracy, perceived control, positive illusions and past investment success. The formative assessments revealed that positive illusions followed by past investment success among retail investors played an instrumental role in orchestrating the OBs that affect investment decisions in financial markets.

The formative index of OB has several practical implications for registered financial and investment advisors, bank advisors, business media companies and portfolio managers, besides individual investors in the domain of behavioral finance.

This research provides a novel approach to provide a formative index of OB with four dimensions. This formative index can acts as an overview for upcoming researchers to investigate the OB of retail individual investors.

1. Overconfidence bias is an important predictor of retail investors' behavior

2. Formative dimensions of the overconfidence bias index.

3. Accuracy, perceived control, positive illusions and past investment success are important dimensions of overconfidence bias.

4. Modern portfolio theory and illusion of control theory support this study.

Overconfidence bias is an important predictor of retail investors' behavior

Formative dimensions of the overconfidence bias index.

Accuracy, perceived control, positive illusions and past investment success are important dimensions of overconfidence bias.

Modern portfolio theory and illusion of control theory support this study.

The purpose of this study is to extend sales control research to inside sales. Aside from a few notable exceptions (Conde et al., 2022) much of the sales control literature has focused on a single control mechanism rather than a sales control portfolio perspective. The authors add multiple layers to Conde et al. (2022) by capturing secondary operational data and manager interviews to access sales control theory in practice.

With operational data from a Fortune 100 financial services company and sales manager interviews, the authors present evidence that managers apply a portfolio of controls to ensure sales agents’ overall performance.

Findings support that cultural controls have a greater influence on overall performance than a focus solely on process and outcome controls. Inside sales managers can generate better results when they focus on creating an employee-centric culture rather than controlling sales agents with formal sales controls.

This study extends sales control research by examining inside sales managers’ formal and informal sales controls. Historically, inside sales had sales leaders balance a myriad of sales controls grounded in strict oversight. With a few notable exceptions, the limited inside sales control research provides the opportunity to display an inside sales manager’s need to jointly focus on operational results and sales outcomes, illustrating the importance of cultural controls compared to other sales process and outcome controls. This research considerably extends sales controls research by focusing on inside sales.

In this digital age, the rapid technological innovation and adoption, with the increasing use of big data analytics, has raised concerns about the ability of small and medium enterprises (SMEs) to sustain the competition and innovation performance (IP). To narrow the research gap, this paper investigates the role of big data analytics capability (BDAC) in moderating the relationship between digital innovation (DI) and SME innovation performance.

This research has been carried forward through a detailed theory and literature analysis. Data were analyzed through confirmatory factor analysis and structural equation models using a two-stage approach in smartPLS-4.

Results highlight that digital service capability (DSC) significantly mediates the relationship between DI and IP. Additionally, value co-creation (VCC) directly affects digital transformation (DT), while DI has a stronger effect on DSC than IP. Furthermore, BDAC significantly moderates the relation between DSC → IP and DT → IP, whereas it has a detrimental effect on the relation between DI and IP. In addition to that, VCC, DSC, DT, DI and BDAC have a direct, significant and positive effect on IP.

This research was motivated by the practical relevance of supporting SMEs in adopting DT and the resource-based view (RBV) and technology acceptance model (TAM). This study shows that all direct and indirect measures significantly affect innovation performance, including BDAC as moderator. These findings refresh the perspective on what DT, DI, VCC, DSC and BDAC can bring to a firm's innovation performance.

This paper has contributed to DT by empirically validating a theoretical argument that suggests the acceptance and adoption of new technology. This paper aims to fill theoretical gaps in understanding BDAC and DT by incorporating the RBV and TAM theories on BDAC and DT.

In response to the problem of insufficient traction/braking adhesion force caused by the existence of the third-body medium on the rail surface, this study aims to analyze the utilization of wheel-rail adhesion coefficient under different medium conditions and propose relevant measures for reasonable and optimized utilization of adhesion to ensure the traction/braking performance and operation safety of trains.

Based on the PLS-160 wheel-rail adhesion simulation test rig, the study investigates the variation patterns of maximum utilized adhesion characteristics on the rail surface under different conditions of small creepage and large slip. Through statistical analysis of multiple sets of experimental data, the statistical distribution patterns of maximum utilized adhesion on the rail surface are obtained, and a method for analyzing wheel-rail adhesion redundancy based on normal distribution is proposed. The study analyzes the utilization of traction/braking adhesion, as well as adhesion redundancy, for different medium under small creepage and large slip conditions. Based on these findings, relevant measures for the reasonable and optimized utilization of adhesion are derived.

When the third-body medium exists on the rail surface, the train should adopt the low-level service braking to avoid the braking skidding by extending the braking distance. Compared with the current adhesion control strategy of small creepage, adopting appropriate strategies to control the train’s adhesion coefficient near the second peak point of the adhesion coefficient-slip ratio curve in large slip can effectively improve the traction/braking adhesion redundancy and the upper limit of adhesion utilization, thereby ensuring the traction/braking performance and operation safety of the train.

Most existing studies focus on the wheel-rail adhesion coefficient values and variation patterns under different medium conditions, without considering whether the rail surface with different medium can provide sufficient traction/braking utilized adhesion coefficient for the train. Therefore, there is a risk of traction overspeeding/braking skidding. This study analyzes whether the rail surface with different medium can provide sufficient traction/braking utilized adhesion coefficient for the train and whether there is redundancy. Based on these findings, relevant measures for the reasonable and optimized utilization of adhesion are derived to further ensure operation safety of the train.

In times of crisis, such as the Covid-19 global pandemic, journalists who write about biomedical information must have the strategic aim to be clearly and easily understood by everyone. In this study, we assume that journalistic discourse could benefit from language redundancy to improve clarity and simplicity aimed at science popularization. The concept of language redundancy is theoretically discussed with the support of discourse analysis and information theory. The methodology adopted is a corpus-based qualitative approach. Two corpora samples with Brazilian Portuguese (BP) texts on Covid-19 were collected. One with texts from a monthly science digital magazine called Pesquisa FAPESP aimed at students and researchers for scientific information dissemination and the other with popular language texts from a news Portal G1 (Rede Globo) aimed at unspecified and/or non-specialized readers. The materials were filtered with two descriptors: “vaccine” and “test.” Preliminary analysis of examples from these materials revealed two categories of redundancy: paraphrastic and polysemic. Paraphrastic redundancy is based on concomitant language reformulation of words, sentences, text excerpts, or even larger units. Polysemic redundancy does not easily show material evidence, but is based on cognitively predictable semantic association in socio-cultural domains. Both kinds of redundancy contribute, each in their own way, to improving text readability for science popularization in Brazil.

This paper aims to provide a reference for the development of digital transformation from the perspective of manufacturing process links.

This paper applies canonical correlation analysis based on digital technology patents in the key links of manufacturing industries (product design, procurement, product manufacturing, warehousing and transportation, and wholesale and retail) and the related indicators of economic benefits of regions in China.

(1) The degree of digitalization of manufacturing process links is significantly correlated with economic benefits. (2) The improvement of the degree of digitalization in the “product design” link, the “warehousing and transportation” link, the “product manufacturing” link and the “wholesale and retail” link has significant impacts on the economic benefits of manufacturing industry. (3) The digital degree of the “procurement” link has no obvious influence on the economic benefits of manufacturing industry.

The research results can provide reference for the formulation and implementation of micro policies. The strategy of improving the level of digital transformation of key links of manufacturing industry is put forward to better promote both the digital transformation of manufacturing industry and economic development.

This paper innovatively studies the relationship between digitalization of manufacturing process links and economic benefits. The findings can provide theoretical and empirical support for the digital transformation of China's manufacturing industry and high-quality development of economy.

This study aims to evaluate the usage of partial least squares structural equation modeling (PLS-SEM) in journals related to logistics and supply chain management (LSCM).

Based on a structured literature review approach, the authors reviewed 401 articles in the field of LSCM applying PLS-SEM published in 15 major journals between 2014 and 2022. The analysis focused on reasons for using PLS-SEM, measurement model and structural model evaluation criteria, advanced analysis techniques and reporting practices.

LSCM researchers sometimes did not clarify the reasons for using PLS-SEM, such as sample size, complex models and non-normal distributions. Additionally, most articles exhibit limited use of measurement models and structural model evaluation techniques, leading to inappropriate use of assessment criteria. Furthermore, progress in the practical implementation of advanced analysis techniques is slow, and there is a need for improved transparency in reporting analysis algorithms.

This study contributes to the field of LSCM by providing clear criteria and steps for using PLS-SEM, enriching the understanding and advancement of research methodologies in this field.