Sami Shahid, Ziyang Zhen and Umair Javaid
Multi-unmanned aerial vehicle (UAV) systems have succeeded in gaining the attention of researchers in diversified fields, especially in the past decade, owing to their capability…
Abstract
Purpose
Multi-unmanned aerial vehicle (UAV) systems have succeeded in gaining the attention of researchers in diversified fields, especially in the past decade, owing to their capability to operate in complex scenarios in a coordinated manner. Path planning for UAV swarms is a challenging task depending upon the environmental conditions, the limitations of fixed-wing UAVs and the swarm constraints. Multiple optimization techniques have been studied for path-planning problems. However, there are local optimum and convergence rate problems. This study aims to propose a multi-UAV cooperative path planning (CoPP) scheme with four-dimensional collision avoidance and simultaneous arrival time.
Design/methodology/approach
A new two-step optimization algorithm is developed based on multiple populations (MP) of disturbance-based modified grey-wolf optimizer (DMGWO). The optimization is performed based on the objective function subject to multi constraints, including collision avoidance, same minimum time of flight and threat and obstacle avoidance in the terrain while meeting the UAV constraints. Comparative simulations using two different algorithms are performed to authenticate the proposed DMGWO.
Findings
The critical features of the proposed MP-DMGWO-based CoPP algorithm are local optimum avoidance and rapid convergence of the solution, i.e. fewer iterations as compared to the comparative algorithms. The efficiency of the proposed method is evident from the comparative simulation results.
Originality/value
A new algorithm DMGWO is proposed for the CoPP problem of UAV swarm. The local best position of each wolf is used in addition to GWO. Besides, a disturbance is introduced in the best solutions for faster convergence and local optimum avoidance. The path optimization is performed based on a newly designed objective function that depends upon multiple constraints.
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Sobia Bano, Muhammad Zeeshan Mirza, Marva Sohail and Muhammad Umair Javaid
The coronavirus disease 2019 (COVID-19) epidemic has given an upsurge to online retailing in Pakistan. This shift has escalated the issues about privacy concerns among consumers…
Abstract
Purpose
The coronavirus disease 2019 (COVID-19) epidemic has given an upsurge to online retailing in Pakistan. This shift has escalated the issues about privacy concerns among consumers. Keeping in view the growing concerns, the objective of this study is to investigate customer patronage in online shopping and the role of privacy concerns in this relationship.
Design/methodology/approach
To generalize the relationship between antecedents and outcomes of privacy concerns, a cross-disciplinary macro model was used. Data were collected through a survey method from the consumers who used credit and debit cards during online shopping.
Findings
Results show that government regulations have a significant positive relationship with privacy concerns and customer patronage. Privacy concerns are found to have a significant negative relationship with organizational ethical care while customer patronage was found to have a significant positive relationship with organizational ethical care. Customer patronage was also found to have a significant negative relationship with privacy concerns. Privacy concerns mediated the relationship between government regulations and customer patronage, whereas privacy concerns does not mediate the relationship between organizational ethical care and customer patronage.
Originality/value
The research adds to the existing literature and highlights the customer behavior toward online shopping/e-commerce in developing economies. The research gives a direction to stakeholders to counter privacy concerns and ensure safer e-commerce practices.
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Khahan Na-Nan, Jamnean Joungtrakul, Ian David Smith and Ekkasit Sanamthong
To develop and validate an instrument to measure the problems associated with performance appraisal.
Abstract
Purpose
To develop and validate an instrument to measure the problems associated with performance appraisal.
Design/methodology/approach
The implementation was in two phases. Phase 1 involved the development and validation of an instrument to measure the problems with performance appraisal. Phase 2 involved the exploration and confirm the construct measurement. Data used in Phase 1 were collected from interviews with administrators and employees in the automotive parts manufacturing industry and five experts. In Phase 2, data were derived from questionnaires sent to 320 employees of automotive parts manufacturers in the Eastern Region of Thailand.
Findings
Problems concerning performance appraisals were classified into two components as problems with the appraisal process and problems with the appraising person. The concepts, theories and interview results that were used to develop the instrument and assess problems with performance appraisals were consistent with the empirical evidence.
Practical implications
The developed instrument may be used to measure problem levels of performance appraisals in organizations with high accuracy and reliability. Findings may be used as guidelines for management to effectively reduce problems with performance appraisals. The instrument may also be used for research measurement of organizational problems concerning performance appraisal.
Social implications
Fairness, transparency and testability are aspects of effective management. Ignorance of problems in performance appraisals may have negative effects on a conducive working atmosphere and behaviors at the personal, group and organizational levels. Therefore, the findings of this study have social implications for the capability to examine fairness in employees' performance appraisals.
Originality/value
The instrument for measuring problems with performance appraisal was developed based on the combination of concepts, theories and interview and questionnaire data. This instrument facilitates human resource officers, managers and organizations in measuring the levels of problems with performance appraisals.
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Shrawan Kumar Trivedi, Jaya Srivastava, Pradipta Patra, Shefali Singh and Debashish Jena
In current era, retaining the best-performing employees has become essential for businesses to compete in the dynamic technological landscape. Consequently, organizations must…
Abstract
Purpose
In current era, retaining the best-performing employees has become essential for businesses to compete in the dynamic technological landscape. Consequently, organizations must ensure that their star performers believe that company’s reward and recognition (R&R) system is fair and equal. This study aims to use an explainable machine learning (eXML) model to develop a prediction algorithm for employee satisfaction with the fairness of R&R systems.
Design/methodology/approach
The current study uses state-of-the-art machine learning models such as Naive Bayes, Decision Tree C5.0, Random Forest and support vector machine-RBF to predict employee satisfaction towards fairness in R&R. The primary data used in the study has been collected from the employees of a large public sector undertaking from an emerging economy. This study also proposes a novel improved Naïve Bayes (INB) algorithm, the efficiency of which is compared with the state-of-the-art algorithms.
Findings
It is seen that the proposed INB model outperforms the state-of-the-art algorithms in many scenarios. Further, the proposed model and feature interaction are explained using the explainable machine learning (XML) concept. In addition, this study incorporates text mining techniques to corroborate the results from XML and suggests that “Transparency”, “Recognition”, “Unbiasedness”, “Appreciation” and “Timeliness in reward” are the most important features that impact employee satisfaction.
Originality/value
To the best of the authors’ knowledge, this is one of the first studies to use INB algorithm and mixed method research (text mining along with machine learning algorithms) for the prediction of employee satisfaction with respect to the R&R system.
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Muhammad Umair, Muhammad Usman Javaid, Yasir Nawab, Madeha Jabbar, Shagufta Riaz, Hafiz Affan Abid and Khubab Shaker
This paper aims to investigate the influence of picking sequence, weave design and weft yarn material on the thermal conductivity of the woven fabrics.
Abstract
Purpose
This paper aims to investigate the influence of picking sequence, weave design and weft yarn material on the thermal conductivity of the woven fabrics.
Design/methodology/approach
This work includes the development of 36 woven samples with two weave designs (1/1 plain and 3/1 twill), three picking sequences (single, double and three pick insertion) and six different weft yarn materials (cotton, polyester having 48 filaments, polyester with 144 filaments, spun coolmax having Lycra in core and coolmax in sheath, filament coolmax and polypropylene). The thermal conductivity was measured using ALAMBETA tester.
Findings
The results showed that weft yarn material, weave design and picking sequence have a meaningful impact on the thermal conductivity of woven fabric. The value of thermal conductivity was lowest for the fabrics with three pick insertion and 3/1 twill weave in all weft yarn materials.
Research limitations/implications
Plain woven fabric with single pick insertion is feasible for summer wear to enhance the comfort of wearer. By changing the warp yarn grouping and material, improved thermal conductivity/resistance can also be achieved.
Originality/value
The authors have studied the combined effect of different weft yarn materials with different picking sequences and different weave designs on thermal conductivity of the woven fabrics.
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Muhammad Umar Nazir, Muhammad Usman Javaid, Khubab Shaker, Yasir Nawab, Tanveer Hussain and Muhammad Umair
This paper aims to develop bilayer woven fabrics with different picking sequences with enhanced comfort without any change in the constituent materials.
Abstract
Purpose
This paper aims to develop bilayer woven fabrics with different picking sequences with enhanced comfort without any change in the constituent materials.
Design/methodology/approach
Six bilayer woven fabrics were produced on Dobby loom with 3/1 twill weave using micro-polyester yarn. Three different picking sequences, i.e. single pick insertion (SPI), double pick insertion (DPI) and three pick insertion (3PI), were used in both face and back layers. The effect of picking sequence on air permeability (AP), volume porosity, thermal resistance and overall moisture management capability (OMMC) of the samples were analyzed.
Findings
The results showed that 3PI–3PI picking sequence gives the highest OMMC, AP and thermal resistance in bilayer woven fabrics and the least results exhibited by SPI–SPI picking sequence.
Research limitations/implications
This research uses a bilayer woven system that develops channels and trapes the air causing higher thermal resistance; therefore, applicable for winter sports clothing rather than for summer wear. Developed bilayer woven fabrics can be used in winter sportswear to improve the comfort of the wearer and reduce fatigue during activity.
Originality/value
Authors have developed bilayer fabrics by changing the picking sequences, i.e. SPI, DPI and 3PI of weft yarns in both layers and compared their thermo-physiological comfort properties.
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Shahbaz Sharif, Omaima Munawar Albadry, Muhammad Kashif Durrani and Muhammad Hamid Shahbaz
Employees are driven and motivated to exercise knowledge-based resources as a result of leadership. Therefore, this study aims to examine the effect of authentic leadership on…
Abstract
Purpose
Employees are driven and motivated to exercise knowledge-based resources as a result of leadership. Therefore, this study aims to examine the effect of authentic leadership on organizational commitment and tacit and explicit knowledge-sharing behaviors in Saudi non-profit organizations (NPOs). The study also aims to explore authentic leadership’s direct and indirect impact on tacit and explicit knowledge-sharing behaviors via organizational commitment.
Design/methodology/approach
The study used a quantitative research design by distributing a survey questionnaire among 415 employees. A total of 300 responses were collected during the survey questionnaire data collection.
Findings
The results showed that authentic leadership significantly and positively influenced organizational commitment and tacit and explicit knowledge sharing. Additionally, organizational commitment significantly and positively mediated the relationship between authentic leadership and tacit knowledge sharing, and there was partial mediation. However, organizational commitment failed to mediate the relationship between authentic leadership and explicit knowledge sharing.
Practical implications
The management of Saudi NPOs should focus on developing knowledge capital resources for employees who work in an organization to get a competitive advantage.
Originality/value
The study made a novel contribution that the Saudi NPOs should promote tacit and explicit knowledge-sharing but focus more on explicit knowledge sharing.
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Omar Javaid, Aamir Feroz Shamsi and Irfan Hyder
There are many entrepreneurial communities in the Asian subcontinent, which are known for their economic resilience and religious orientation but have received limited attention…
Abstract
Purpose
There are many entrepreneurial communities in the Asian subcontinent, which are known for their economic resilience and religious orientation but have received limited attention in extant literature. These communities include Memon, Delhiwala, Chinioti, Ismaili and Bohri, which have been persistent in keeping their members economically stable, as many centuries, while also retaining their religio-sociocultural identity. This paper aims to add to the body of literature by documenting the possible factors, which contribute toward advancing socio-economic justice for the members of respective communities.
Design/methodology/approach
This study uses Eisenhardth research strategy within a social constructivist paradigm to process data from in-depth interviews, memos and documentary sources to explore the internal dynamics of three most prominent of these communities (Memon, Delhiwala and Chinioti) in Pakistan.
Findings
The findings reveal that the secret to their resilience is, perhaps, rooted in their religio-sociocultural communal norms, which may not just ensure effective wealth redistribution among the deserving segments of the society but may also enable its deserving members to achieve self-reliance through community-supported–entrepreneurial–activity. This study proposes that a culture of community-based–family–entrepreneurship coupled with the spirit of cooperation, sacrifice and reciprocity may eliminate the possibility of socioeconomic injustice.
Social implications
The religious entrepreneurial communities may be seen as an alternate to free-market or state-driven methods to impart socioeconomic justice where needed. The voluntary inclination of entrepreneurs in such communities to facilitate those in need may, perhaps, reduce or even eliminate the need to involve state intervention to redistribute wealth through taxation, which may also eliminate the cost of the state bureaucracy, which is used for the collection and redistribution of taxes.
Originality/value
The findings add to the body of literature which could help similar communities to improve their socioeconomic stability in a just manner for all its members. Policymakers can also take notice of the religio-sociocultural norms at the source of socioeconomic justice within the respective communities to formulate policies conducive to sustaining such norms where necessary.
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Subhodeep Mukherjee, Manish Mohan Baral, Venkataiah Chittipaka, Ramji Nagariya and Bharat Singh Patel
This research investigates the adoption of the industrial Internet of things (IIoT) in SMEs to achieve and increase organizational performance. With the latest technology, small…
Abstract
Purpose
This research investigates the adoption of the industrial Internet of things (IIoT) in SMEs to achieve and increase organizational performance. With the latest technology, small and medium-sized enterprises (SMEs) can create a competitive edge in the market and better serve customers.
Design/methodology/approach
Twelve hypotheses are proposed for this study. This study constructed a questionnaire based on technological, organizational, environmental and human perspectives. A survey is conducted on the SMEs of India using the questionnaire.
Findings
Eight hypotheses were accepted, and four hypotheses were not supported. The hypotheses rejected are infrastructure, organizational readiness, internal excellence and prior experience. The findings suggested that adopting IIoT in SMEs will increase organizational performance.
Research limitations/implications
This study will be helpful for the manager, top management and policymakers. This study identified the areas SMEs need to work on to adopt the technologies.
Originality/value
In the literature, no article considered IIoT adoption in SME firms as a human factor. Therefore, this study is unique, including human, technological, organizational and environmental factors.
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Shweta V. Matey, Dadarao N. Raut, Rajesh B. Pansare and Ravi Kant
Blockchain technology (BCT) can play a vital role in manufacturing industries by providing visibility and real-time transparency. With BCT adoption, manufacturers can achieve…
Abstract
Purpose
Blockchain technology (BCT) can play a vital role in manufacturing industries by providing visibility and real-time transparency. With BCT adoption, manufacturers can achieve higher productivity, better quality, flexibility and cost-effectiveness. The current study aims to prioritize the performance metrics and ranking of enablers that may influence the adoption of BCT in manufacturing industries through a hybrid framework.
Design/methodology/approach
Through an extensive literature review, 4 major criteria with 26 enablers were identified. Pythagorean fuzzy analytical hierarchy process (AHP) method was used to compute the weights of the enablers and the Pythagorean fuzzy combined compromise solution (Co-Co-So) method was used to prioritize the 17-performance metrics. Sensitivity analysis was then carried out to check the robustness of the developed framework.
Findings
According to the results, data security enablers were the most significant among the major criteria, followed by technology-oriented enablers, sustainability and human resources and quality-related enablers. Further, the ranking of performance metrics shows that data hacking complaints per year, data storage capacity and number of advanced technologies available for BCT are the top three important performance metrics. Framework robustness was confirmed by sensitivity analysis.
Practical implications
The developed framework will contribute to understanding and simplifying the BCT implementation process in manufacturing industries to a significant level. Practitioners and managers may use the developed framework to facilitate BCT adoption and evaluate the performance of the manufacturing system.
Originality/value
This study can be considered as the first attempt to the best of the author’s knowledge as no such hybrid framework combining enablers and performance indicators was developed earlier.