Search results
1 – 10 of over 2000Joseph F. Hair, Pratyush N. Sharma, Marko Sarstedt, Christian M. Ringle and Benjamin D. Liengaard
The purpose of this paper is to assess the appropriateness of equal weights estimation (sumscores) and the application of the composite equivalence index (CEI) vis-à-vis…
Abstract
Purpose
The purpose of this paper is to assess the appropriateness of equal weights estimation (sumscores) and the application of the composite equivalence index (CEI) vis-à-vis differentiated indicator weights produced by partial least squares structural equation modeling (PLS-SEM).
Design/methodology/approach
The authors rely on prior literature as well as empirical illustrations and a simulation study to assess the efficacy of equal weights estimation and the CEI.
Findings
The results show that the CEI lacks discriminatory power, and its use can lead to major differences in structural model estimates, conceals measurement model issues and almost always leads to inferior out-of-sample predictive accuracy compared to differentiated weights produced by PLS-SEM.
Research limitations/implications
In light of its manifold conceptual and empirical limitations, the authors advise against the use of the CEI. Its adoption and the routine use of equal weights estimation could adversely affect the validity of measurement and structural model results and understate structural model predictive accuracy. Although this study shows that the CEI is an unsuitable metric to decide between equal weights and differentiated weights, it does not propose another means for such a comparison.
Practical implications
The results suggest that researchers and practitioners should prefer differentiated indicator weights such as those produced by PLS-SEM over equal weights.
Originality/value
To the best of the authors’ knowledge, this study is the first to provide a comprehensive assessment of the CEI’s usefulness. The results provide guidance for researchers considering using equal indicator weights instead of PLS-SEM-based weighted indicators.
Details
Keywords
This paper aims to help understand how adopting risk allocation criteria impacts the delivery of public–private partnership (PPP) mass housing in Nigeria with the view of…
Abstract
Purpose
This paper aims to help understand how adopting risk allocation criteria impacts the delivery of public–private partnership (PPP) mass housing in Nigeria with the view of promoting the adoption of PPP housing scheme in Nigeria.
Design/methodology/approach
The research design adopts the census sampling approach by using well-structured questionnaires distributed to stakeholders involved in PPP-procured mass housing projects, i.e. consultants, in-house professionals, contractors and the organized private sector, registered with PPP departments in the Federal Capital Territory Development Authority, Abuja, Nigeria. Sixty-three risk factors, nine risk allocation criteria and nine project delivery indices were submitted for the respondents to rank on a Likert scale of 7. Two hypotheses were formulated to test whether the risk allocation criteria impacted PPP mass housing delivery or otherwise. The study adopts partial least square-structural equation modeling to model the effect of risk on risk allocation criteria on project delivery indices and risk severity.
Findings
The finding shows that project risk allocation criteria have less effect on project delivery indices than on risk severity. The study concludes that risk allocation principles do not directly affect the delivery of PPP-procured mass housing projects. This is evident by the path coefficient of 0.724 values, which is not statistically significant at a 5% alpha protection value. The study concludes that allocating critical risk factors influences the performance of PPP-procured mass housing projects, as the path coefficient of 0.360 is also not significantly far from 0 and at a 5% alpha protection value.
Originality/value
The study is one of the recent studies conducted in PPP-procured mass housing projects in Nigeria owing to the novelty of procurement option in the sector. It highlights the risk factors that can jeopardize the PPP-procured mass housing project objectives. The study is of immense value to PPP actors in the sector by providing the necessary information required to formulate risk response methods to minimize the impact of the risk factors in PPP mass housing projects.
Details
Keywords
Hakeem A. Owolabi, Azeez A. Oyedele, Lukumon Oyedele, Hafiz Alaka, Oladimeji Olawale, Oluseyi Aju, Lukman Akanbi and Sikiru Ganiyu
Despite an enormous body of literature on conflict management, intra-group conflicts vis-à-vis team performance, there is currently no study investigating the conflict prevention…
Abstract
Purpose
Despite an enormous body of literature on conflict management, intra-group conflicts vis-à-vis team performance, there is currently no study investigating the conflict prevention approach to handling innovation-induced conflicts that may hinder smooth implementation of big data technology in project teams.
Design/methodology/approach
This study uses constructs from conflict theory, and team power relations to develop an explanatory framework. The study proceeded to formulate theoretical hypotheses from task-conflict, process-conflict, relationship and team power conflict. The hypotheses were tested using Partial Least Square Structural Equation Model (PLS-SEM) to understand key preventive measures that can encourage conflict prevention in project teams when implementing big data technology.
Findings
Results from the structural model validated six out of seven theoretical hypotheses and identified Relationship Conflict Prevention as the most important factor for promoting smooth implementation of Big Data Analytics technology in project teams. This is followed by power-conflict prevention, prevention of task disputes and prevention of Process conflicts respectively. Results also show that relationship and power conflicts interact on the one hand, while task and relationship conflict prevention also interact on the other hand, thus, suggesting the prevention of one of the conflicts could minimise the outbreak of the other.
Research limitations/implications
The study has been conducted within the context of big data adoption in a project-based work environment and the need to prevent innovation-induced conflicts in teams. Similarly, the research participants examined are stakeholders within UK projected-based organisations.
Practical implications
The study urges organisations wishing to embrace big data innovation to evolve a multipronged approach for facilitating smooth implementation through prevention of conflicts among project frontlines. This study urges organisations to anticipate both subtle and overt frictions that can undermine relationships and team dynamics, effective task performance, derail processes and create unhealthy rivalry that undermines cooperation and collaboration in the team.
Social implications
The study also addresses the uncertainty and disruption that big data technology presents to employees in teams and explore conflict prevention measure which can be used to mitigate such in project teams.
Originality/value
The study proposes a Structural Model for establishing conflict prevention strategies in project teams through a multidimensional framework that combines constructs like team power conflict, process, relationship and task conflicts; to encourage Big Data implementation.
Details
Keywords
Ankur Kumar, Ambika Srivastava and Subhas C. Misra
The purpose of this study is to investigate the influence that technological, environmental and organizational factors have on the rate of Internet of Things (IoT) adoption within…
Abstract
Purpose
The purpose of this study is to investigate the influence that technological, environmental and organizational factors have on the rate of Internet of Things (IoT) adoption within the logistics industry. In addition, the moderating effect that the risk factor has on the technological, environmental and organizational factors regarding the implementation of IoT in logistics.
Design/methodology/approach
For the purpose of testing the models and hypotheses, a survey was carried out in order to collect the responses from currently employed individuals at various companies working in the field of logistics or IoT. For the purpose of analysis, the authors made use of the partial least squares structure equation model (PLS-SEM) technique.
Findings
Findings of this study concluded that technology- and environmental-related factors significantly affect the adoption of IoT in logistics, while risk acts as a moderator for the technological-related factor only in the adoption of IoT in logistics.
Research limitations/implications
The relevance of the authors' study lies in the growing importance of IoT in logistics and the need for logistics companies to understand the factors that impact the adoption of IoT in their operations. By identifying and analyzing the factors that influence IoT adoption in logistics, the authors' study provides valuable insights that can help logistics companies make informed decisions about whether and how to adopt IoT.
Practical implications
The research will help organizations make strategies for the successful adoption of IoT and ease the lives of all the stakeholders.
Originality/value
In this research, the authors attempted to find the factors that influence the adoption of IoT in logistics management. The influence of the technological, environmental, organizational and risk-related factors on the adoption of IoT in logistics management was studied. The moderating effect of risk over these factors on the adoption of IoT in logistics was also analyzed. This is original work and has never been done earlier.
Details
Keywords
Puja Khatri, Harshleen Kaur Duggal, Sumedha Dutta, Preeti Kumari, Asha Thomas, Tatyana Brod and Letizia Colimoro
With new hybrid working models in place post COVID-19, it is requisite that knowledge workers (KWs) stay agile. Knowledge-oriented leadership (KOL) can help employees with…
Abstract
Purpose
With new hybrid working models in place post COVID-19, it is requisite that knowledge workers (KWs) stay agile. Knowledge-oriented leadership (KOL) can help employees with essential knowledge acquisition (KA) facilitating the journey toward hybrid work agility (HWA). This study, thus, aims to explore the impact of KOL and KA on HWA and reveal whether this effect stems uniformly from a single homogenous population or if there is unobserved heterogeneity leading to identifiable segments of agile KWs.
Design/methodology/approach
Data was collected through stratified sampling from 416 employees from 20 information technology enabled services companies involved in knowledge-intensive tasks. Partial least squares (PLS) structural equation modeling approach, using SMART PLS 4.0, has been applied to examine the effect of KOL and KA on HWA. Finite mixture PLS, PLS prediction-oriented segmentation and multigroup analysis have been used to identify segments, test segment-specific path models and analyze the significance of the differences in the path coefficients for unobserved heterogeneity. Predictive relevance of the model has been determined using PLS Predict.
Findings
Results indicate that KOL contributes to employees’ KA and HWA. A significant positive relationship is also reported between KA and HWA. The model has medium predictive relevance. A two-segment solution has been delineated, wherein independent agile KWs (who value autonomy and personal agency over leadership for KA) and dependent agile KWs (who depend on leaders for relational and structural support for KA) have been identified. Thus, KOL and KA play a differential role in determining HWA.
Research limitations/implications
The authors’ major contribution to the knowledge body constitutes the determination of antecedents of HWA and a typology of agile KWs. Future researchers may conduct segment-wise qualitative analysis to delineate other variables that contribute to HWA.
Practical implications
Technological advances necessitate that knowledge-intensive industries foster agility in employees for strategic agility of the organization. For effecting agile adaption of an organization to the knowledge economy conditions, it is pertinent that the full potential of this human resource be used. By profiling HWA of KWs on the basis of dimensions of KOL and the level of their KA, organizations will be able to help employees adapt better to rapidly changing work conditions.
Originality/value
HWA is a novel concept and very germane in a hybrid working environment. To the best of the authors’ knowledge, this is the first study to examine the effects of the dimensions of KOL and KA in relation to HWA, along with an empirical examination of unobserved heterogeneity in the aforementioned relationship.
Details
Keywords
Luqman Oyewobi, Taofeek Tunde Okanlawon, Kabir Ibrahim and Richard Ajayi Jimoh
The construction industry faces public criticism for issues like wastefulness, inefficiency, slim profits, scheduling setbacks, budget overruns, quality concerns, trust deficits…
Abstract
Purpose
The construction industry faces public criticism for issues like wastefulness, inefficiency, slim profits, scheduling setbacks, budget overruns, quality concerns, trust deficits, transparency, coordination, communication and fraud. This paper aims to assess the nexus between barriers and drivers for adopting blockchain in construction and its impact on construction lifecycle.
Design/methodology/approach
A quantitative research approach was used to collect data using a well-structured questionnaire survey. The survey, which used snowball sampling, included 155 Nigerian construction experts that included architects, builders, quantity surveyors and engineers in the built environment. The data were analysed using partial least squares structural equation modelling (PLS-SEM), which allowed for a thorough evaluation of the proposed relationships as well as industry-specific insights.
Findings
The study's findings validate the conceptual framework established. The results indicate that implementing blockchain across all stages of construction projects has the potential to improve the construction process by 88.2% through its drivers. However, there were no significant relationships found between the barriers to adopting blockchain and the potential application areas in the construction lifecycle.
Research limitations/implications
This research was carried out in the South-western which is one of the six geo-political zones/regions in Nigeria, using a cross-sectional survey method. The study did not investigate the interdependence of the identified categories of drivers and barriers, limiting a comprehensive understanding of the complex dynamics and interactions influencing blockchain adoption in construction. The study is expected to stimulate further exploration and generate new insights on how blockchain technology (BT) can influence various stages of the construction lifecycle.
Practical implications
The findings will be immensely beneficial to both professionals and practitioners in the Nigerian construction industry in learning about the potential of BT application in improving the construction lifecycle.
Originality/value
This paper developed and assessed a conceptual framework by investigating the interrelationships between the constructs. The findings have important implications for the construction industry, as they offer opportunities to improve the construction process and overall lifecycle. The findings are useful for researchers interested in the potential impact of BT on the construction lifecycle and its wider implications.
Details
Keywords
David Asamoah, Benjamin Agyei-Owusu, Dorcas Nuertey, Caleb Amankwaa Kumi, Joseph Akyeh and Prince Delali Fiadjoe
This study provides new insights into antecedents and outcomes of reverse logistics practices by examining green customer salience as the driver of reverse logistics practices and…
Abstract
Purpose
This study provides new insights into antecedents and outcomes of reverse logistics practices by examining green customer salience as the driver of reverse logistics practices and examining environmental performance and green firm reputation as the outcomes of reverse logistics practices.
Design/methodology/approach
A research model examining the proposed relationships was developed and tested using data from beverage manufacturers in Ghana. The model was analysed using partial least squares structural equation modelling.
Findings
This study confirmed that green customer salience drives reverse logistics practices. It was also revealed that reverse logistics directly enhances environmental performance, but not green firm reputation. Additionally, the effect of reverse logistics on green firm reputation was fully mediated through environmental performance.
Originality/value
To the best of the authors’ knowledge, no previous studies have empirically examined the relationship between green customer salience, reverse logistics, environmental performance and green firm reputation.
Details
Keywords
Emir Malikov, Shunan Zhao and Jingfang Zhang
There is growing empirical evidence that firm heterogeneity is technologically non-neutral. This chapter extends the Gandhi, Navarro, and Rivers (2020) proxy variable framework…
Abstract
There is growing empirical evidence that firm heterogeneity is technologically non-neutral. This chapter extends the Gandhi, Navarro, and Rivers (2020) proxy variable framework for structurally identifying production functions to a more general case when latent firm productivity is multi-dimensional, with both factor-neutral and (biased) factor-augmenting components. Unlike alternative methodologies, the proposed model can be identified under weaker data requirements, notably, without relying on the typically unavailable cross-sectional variation in input prices for instrumentation. When markets are perfectly competitive, point identification is achieved by leveraging the information contained in static optimality conditions, effectively adopting a system-of-equations approach. It is also shown how one can partially identify the non-neutral production technology in the traditional proxy variable framework when firms have market power.
Details
Keywords
In Structural Equation Modelling (SEM) cases, a number of steps to ensure that the measurement of the latent constructs, variables, and indicators have been appropriate, reliable…
Abstract
In Structural Equation Modelling (SEM) cases, a number of steps to ensure that the measurement of the latent constructs, variables, and indicators have been appropriate, reliable, and meet the rules of quantitative research that must be passed by researchers. One of them is the criteria for determining the presence (or not) of a discriminant validity violation, which is still a fierce debate among researchers today. The last recommended method is the Heterotrait–Monotrait ratio of correlation (HTMT) which seeks to revise the previously existing discriminant validity criteria such as the Fornell–Larcker and Cross-loadings criteria. This chapter discusses the implementation of HTMT in the case of manufacturing small and medium enterprises (SMEs) in Indonesia with the aim of providing an illustration of how the HTMT is capable of detecting the violation of discriminant validity and the solutions that can be carried out following the recommendations given by the originators.
Details
Keywords
Mulatu Tilahun Gelaw, Daniel Kitaw Azene and Eshetie Berhan
This research aims to investigate critical success factors, barriers and initiatives of total productive maintenance (TPM) implementation in selected manufacturing industries in…
Abstract
Purpose
This research aims to investigate critical success factors, barriers and initiatives of total productive maintenance (TPM) implementation in selected manufacturing industries in Addis Ababa, Ethiopia.
Design/methodology/approach
This study built and looked into a conceptual research framework. The potential barriers and success factors to TPM implementation have been highlighted. The primary study techniques used to collect relevant data were a closed-ended questionnaire and semi-structured interview questions. With the use of SPSS version 23 and SmartPLS 3.0 software, the data were examined using descriptive statistics and the inferential Partial Least Square Structural Equation Modeling (PLS-SEM) techniques.
Findings
According to the results of descriptive statistics and multivariate analysis using PLS-SEM, the case manufacturing industries' TPM implementation initiative is in its infancy; break down maintenance is the most widely used maintenance policy; top managers are not dedicated to the implementation of TPM; and there are TPM pillars that have been weakly and strongly addressed by the case manufacturing companies.
Research limitations/implications
The small sample size is a limitation to this study. It is therefore challenging to extrapolate the research findings to other industries. The only manufacturing KPI utilized in this study is overall equipment effectiveness (OEE). It is possible to add more parameters to the manufacturing performance measurement KPI. The relationships between TPM and other lean production methods may differ from those observed in this cross-sectional study. Longitudinal experimental studies and in-depth analyses of TPM implementations may shed further light on this.
Practical implications
Defining crucial success factors and barriers to TPM adoption, as well as identifying the weak and strong TPM pillars, will help companies in allocating their scarce resources exclusively to the most important areas. TPM is not a quick solution. It necessitates a change in both the company's and employees' attitude and their values, which takes time to bring about. Hence, it entails a long-term planning. The commitment of top managers is very important in the initiatives of TPM implementation.
Originality/value
This study is unique in that, it uses a new conceptual research model and the PLS-SEM technique to analyze relationships between TPM pillars and OEE in depth.
Details