Nida Malik, Amir Zaib Abbasi, M. Sadiq Sohail, Ghazanfar Ali Abbasi and Ding Hooi Ting
There has been a dramatic rise in the use of online food delivery apps (FDAs) services since the COVID-19 pandemic. Though online FDAs have contributed significantly to the rise…
Abstract
Purpose
There has been a dramatic rise in the use of online food delivery apps (FDAs) services since the COVID-19 pandemic. Though online FDAs have contributed significantly to the rise in demand for products from the gourmet industry, little is known regarding the factors that inspire customers to order from online FDAs, subsequently influencing customers’ satisfaction. Considering the knowledge gap, this study utilizes the stimulus-organism-response (S-O-R) model to conceptualize the factors: stimuli (eWOM, online reviews and online deals as external stimuli, and late-night craving and convenience as internal stimuli) that determine the organism level (i.e. customers’ inspiration) to subsequently generate the response (i.e. customers’ satisfaction).
Design/methodology/approach
We collected the data from 388 users and analyzed it via partial least squares – structural equation modeling (PLS-SEM).
Findings
The results reveal that online reviews, deals, late-night food cravings and convenience positively determine customers’ inspiration and satisfaction. In contrast, eWOM fails to impact customers’ inspiration directly and indirectly, affecting customers’ satisfaction through inspiration. Besides, customers’ inspiration positively mediates the relationship between stimuli (e.g. online reviews, online deals, late-night cravings and convenience) and customers’ satisfaction.
Originality/value
This study is novel in that it explores the impact of internal (late-night craving and convenience) and external (eWOM, online reviews and online deals) stimuli on customer inspiration and subsequently predicts customer satisfaction. We also expand prior studies on food delivery apps by studying customer inspiration as a mediating mechanism between internal and external stimuli and customer satisfaction.
Details
Keywords
M.S.A. ABBASI, M.H. BALUCH, A.K. AZAD and H.H. ABDEL‐RAHMAN
This paper presents the full range sensitivity study of various components of material model on the response of reinforced concrete slabs subjected to central patch loads using…
Abstract
This paper presents the full range sensitivity study of various components of material model on the response of reinforced concrete slabs subjected to central patch loads using non‐linear finite element analysis. A layered degenerate quadratic plate element with five degrees of freedom was employed. Smeared crack model was used with orthogonal cracking. The components considered in this work are: perfectly plastic models versus hardening models, role of crushing condition on collapse load, influence of dowel effect on punching capacity, parametric variation of tension stiffening parameter, parametric variation of degraded shear modulus and the role of yield criterion.
Details
Keywords
Chin How (Norman) Goh, Michael D. Short, Nanthi S. Bolan and Christopher P. Saint
Biosolids, the residual solids from wastewater treatment operations and once considered a waste product by the industry, are now becoming increasingly recognised as a…
Abstract
Biosolids, the residual solids from wastewater treatment operations and once considered a waste product by the industry, are now becoming increasingly recognised as a multifunctional resource with growing opportunities for marketable use. This shift in attitude towards biosolids management is spurred on by increasing volatility in energy, fertilizer and commodity markets as well as moves by the global community towards mitigating global warming and the effects of climate change. This chapter will provide an overview of current global biosolids practices (paired with a number of Australian examples) as well as discuss potential future uses of biosolids. Additionally, present and future risks and opportunities of biosolids use are highlighted, including potential policy implications.
Details
Keywords
Haider Jouma, Muhamad Mansor, Muhamad Safwan Abd Rahman, Yong Jia Ying and Hazlie Mokhlis
This study aims to investigate the daily performance of the proposed microgrid (MG) that comprises photovoltaic, wind turbines and is connected to the main grid. The load demand…
Abstract
Purpose
This study aims to investigate the daily performance of the proposed microgrid (MG) that comprises photovoltaic, wind turbines and is connected to the main grid. The load demand is a residential area that includes 20 houses.
Design/methodology/approach
The daily operational strategy of the proposed MG allows to vend and procure utterly between the main grid and MG. The smart metre of every consumer provides the supplier with the daily consumption pattern which is amended by demand side management (DSM). The daily operational cost (DOC) CO2 emission and other measures are utilized to evaluate the system performance. A grey wolf optimizer was employed to minimize DOC including the cost of procuring energy from the main grid, the emission cost and the revenue of sold energy to the main grid.
Findings
The obtained results of winter and summer days revealed that DSM significantly improved the system performance from the economic and environmental perspectives. With DSM, DOC on winter day was −26.93 ($/kWh) and on summer day, DOC was 10.59 ($/kWh). While without considering DSM, DOC on winter day was −25.42 ($/kWh) and on summer day DOC was 14.95 ($/kWh).
Originality/value
As opposed to previous research that predominantly addressed the long-term operation, the value of the proposed research is to investigate the short-term operation (24-hour) of MG that copes with vital contingencies associated with selling and procuring energy with the main grid considering the environmental cost. Outstandingly, the proposed research engaged the consumers by smart meters to apply demand-sideDSM, while the previous studies largely focused on supply side management.
Details
Keywords
Mohamad Amin Kaviani, Amir Karbassi Yazdi, Lanndon Ocampo and Simonov Kusi-Sarpong
The oil and gas industry is a crucial economic sector for both developed and developing economies. Delays in extraction and refining of these resources would adversely affect…
Abstract
Purpose
The oil and gas industry is a crucial economic sector for both developed and developing economies. Delays in extraction and refining of these resources would adversely affect industrial players, including that of the host countries. Supplier selection is one of the most important decisions taken by managers of this industry that affect their supply chain operations. However, determining suitable suppliers to work with has become a phenomenon faced by these managers and their organizations. Furthermore, identifying relevant, critical and important criteria needed to guide these managers and their organizations for supplier selection decisions has become even more complicated due to various criteria that need to be taken into consideration. With limited works in the current literature of supplier selection in the oil and gas industry having major methodological drawbacks, the purpose of this paper is to develop an integrated approach for supplier selection in the oil and gas industry.
Design/methodology/approach
To address this problem, this paper proposes a new uncertain decision framework. A grey-Delphi approach is first applied to aid in the evaluation and refinement of these various available criteria to obtain the most important and relevant criteria for the oil and gas industry. The grey systems theoretic concept is adopted to address the subjectivity and uncertainty in human judgments. The grey-Shannon entropy approach is used to determine the criteria weights, and finally, the grey-EDAS (evaluation based on distance from average solution) method is utilized for determining the ranking of the suppliers.
Findings
To exemplify the applicability and robustness of the proposed approach, this study uses the oil and gas industry of Iran as a case in point. From the literature review, 21 criteria were established and using the grey-Delphi approach, 16 were finally considered. The four top-ranked criteria, using grey-Shannon entropy, include warranty level and experience time, relationship closeness, supplier’s technical level and risks which are considered as the most critical and influential criteria for supplier evaluation in the Iranian oil and gas industry. The ranking of the suppliers is obtained, and the best and worst suppliers are also identified. Sensitivity analysis indicates that the results using the proposed methodology are robust.
Research limitations/implications
The proposed approach would assist supply chain practicing managers, including purchasing managers, procurement managers and supply chain managers in the oil and gas and other industries, to effectively select suitable suppliers for cooperation. It can also be used for other multi-criteria decision-making (MCDM) applications. Future works on applying other MCDM methods and comparing them with the results of this study can be addressed. Finally, broader and more empirical works are required in the oil and gas industry.
Originality/value
This study is among the first few studies of supplier selection in the oil and gas industry from an emerging economy perspective and sets the stage for future research. The proposed integrated grey-based MCDM approach provides robust results in supplier evaluation and can be used for future domain applications.
Details
Keywords
Rohit Kumar Singh and Sachin Modgil
This paper aims to evaluate and prioritize the key supplier selection indicators and to establish the relationship between available alternatives and selected indicators by using…
Abstract
Purpose
This paper aims to evaluate and prioritize the key supplier selection indicators and to establish the relationship between available alternatives and selected indicators by using step-wise weight assessment ratio analysis (SWARA) and weighted aggregated sum product assessment (WASPAS).
Design/methodology/approach
Authors have extracted the supplier selection criteria from literature and used a combined SWARA-WASPAS method to evaluate and rank the criteria’s. SWARA is applied for evaluating and weighting selection criteria, whereas WASPAS helped in evaluating different available alternatives based on supplier selection indicators.
Findings
Finding from SWARA suggests that supplier management is the high weighted criteria followed by information sharing and joint actions. WASPAS was used to evaluate the available alternatives and supplier A1 got the highest priority. Additionally, sensitivity analysis indicates the different scenarios for the best supplier selection.
Practical implications
Working executives can use the SWARA for assessment of weights of finalized indicators for their firm in the cement industry. Further, the calculated weights can be used for product and sum weightage through WASPAS to finalize the best supplier.
Originality/value
The originality of the manuscript lies in the sector and methodology. Author(s) applied the SWARA and WASPAS method for supplier selection in the Indian cement industry that will help working executives to evaluate their supply chain partners.
Details
Keywords
Mustafizur Rahman, Sifat Ajmeer Haque and Andrea Trianni
This study aims to recognize the significant barriers of small and medium-sized enterprises (SMEs) in Bangladesh, hindering the adoption of total quality management (TQM)…
Abstract
Purpose
This study aims to recognize the significant barriers of small and medium-sized enterprises (SMEs) in Bangladesh, hindering the adoption of total quality management (TQM). Additionally, this research intends to explore the interrelations among these barriers to develop essential managerial insights for promoting TQM implementation in SMEs.
Design/methodology/approach
The interpretive structural modeling (ISM) approach and Matrice d'impacts croisés multiplication appliquée á un classment (MICMAC) a cross-impact matrix multiplication applied to classification show the relationship among the barriers and classification of the barriers to TQM implementation respectively, and partial least squares structural equation modeling (PLS-SEM) is applied for ISM model validation.
Findings
This study examined previous literature and conducted interviews with professionals to identify 17 barriers. The study then develops and investigates a model that outlines the relationships and priorities among these barriers and categorizes them based on their impact and interdependence. This analysis can assist SMEs in implementing TQM during their operations successfully.
Practical implications
This research emphasizes the crucial obstacles that greatly affect other barriers and require immediate attention. Furthermore, this study provides valuable information for SMEs to effectively prioritize their resources and efforts to overcome these obstacles.
Originality/value
This study delves into the primary obstacles impeding the integration of TQM in SMEs through a novel approach. Additionally, this study constructs a verified contextual framework that depicts the hierarchies and interconnections among these barriers.
Details
Keywords
Janak Suthar, Jinil Persis and Ruchita Gupta
Casting is one of the well-known manufacturing processes to make durable parts of goods and machinery. However, the quality of the casting parts depends on the proper choice of…
Abstract
Purpose
Casting is one of the well-known manufacturing processes to make durable parts of goods and machinery. However, the quality of the casting parts depends on the proper choice of process variables related to properties of the materials used in making a mold and the product itself; hence, variables related to product/process designs are taken into consideration. Understanding casting techniques considering significant process variables is critical to achieving better quality castings and helps to improve the productivity of the casting processes. This study aims to understand the computational models developed for achieving better quality castings using various casting techniques.
Design/methodology/approach
A systematic literature review is conducted in the field of casting considering the period 2000–2020. The keyword co-occurrence network and word cloud from the bibliometric analysis and text mining of the articles reveal that optimization and simulation models are extensively developed for various casting techniques, including sand casting, investment casting, die casting and squeeze casting, to improve quality aspects of the casting's product. This study further investigates the optimization and simulation models and has identified various process variables involved in each casting technique that are significantly affecting the outcomes of the processes in terms of defects, mechanical properties, yield, dimensional accuracy and emissions.
Findings
This study has drawn out the need for developing smart casting environments with data-driven modeling that will enable dynamic fine-tuning of the casting processes and help in achieving desired outcomes in today's competitive markets. This study highlights the possible technology interventions across the metal casting processes, which can further enhance the quality of the metal casting products and productivity of the casting processes, which show the future scope of this field.
Research limitations/implications
This paper investigates the body of literature on the contributions of various researchers in producing high-quality casting parts and performs bibliometric analysis on the articles. However, research articles from high-quality journals are considered for the literature analysis in identifying the critical parameters influencing quality of metal castings.
Originality/value
The systematic literature review reveals the analytical models developed using simulation and optimization techniques and the important quality characteristics of the casting products. Further, the study also explores critical influencing parameters involved in every casting process that significantly affects the quality characteristics of the metal castings.
Details
Keywords
Muhammad Bilal Khan, Rehan Zahid, Ali Hussain Kazim and Khalid Javed
Depleting reserves of crude oils and their adverse environmental effects have shifted focus toward environment friendly and biobased lubricant base oils. Natural oils and fats act…
Abstract
Purpose
Depleting reserves of crude oils and their adverse environmental effects have shifted focus toward environment friendly and biobased lubricant base oils. Natural oils and fats act as good lubricants but they have low oxidation and thermal stability which makes them unsuitable for modern day uses. This paper aims to produce trimethylolpropane ester biolubricant from cottonseed oil and study the effects of its use in spark ignition (SI) engines.
Design/methodology/approach
In this work, cottonseed oil is converted to TMP lubricant by a two-step based catalyzed esterification. The lubricants thermophysical properties are then analyzed and a 20% blend with synthetic poly-alpha olefin is used in an spark ignition engine.
Findings
The produced lubricant has viscosity @100oC of 4.91 cSt, a viscosity index of 230 and a flash point of 202oC. When used as a 20% blend in a petrol engine, the rate of oil deterioration was reduced by 18%, however, the overall wear increased by 6.7%. However, this increase is offset by its improved environmental impacts.
Originality/value
In its current state, such a biolubricant can be used as an additive to most commercially available lubricants to improve oil deterioration characteristics and environmental impact. However, further work on improving biolubricant’s wear characteristics is needed for the complete replacement of mineral oil-based lubricants.
Details
Keywords
Surya Prakash, Vijay Prakash Sharma, Ranbir Singh, Lokesh Vijayvargy and Nilaish
This study aims to address the adoption issues of green and sustainable practices in the hotel industry. The study identifies critical performance indicators (CPIs) and utilizes…
Abstract
Purpose
This study aims to address the adoption issues of green and sustainable practices in the hotel industry. The study identifies critical performance indicators (CPIs) and utilizes Hotel Carbon Management Initiative (HCMI) framework to prioritize CPIs for achieving a robust adoption framework for green and sustainable practices.
Design/methodology/approach
The hotel industry is driven by changing ecological degradation, and it is necessary to achieve feasible development goals. This research article formulates the CPIs derived from HCMI and decision-making model is created using the Analytic Hierarchy Process (AHP).
Findings
In this research, CPIs of HCMI are considered and aim to formulate five major CPIs of HCMI, namely air pollution, energy efficiency, water conservation, noise pollution and waste management. The study identifies the need for better control and sustainable growth in the Indian hotel industry with minimum carbon emissions coupled with the green approach adoption.
Research limitations/implications
The CPIs work on minimization of risks and maximizing optimality of return on investment. The development of the hotel industry will be improved and immensely welcomed by capping the carbon emission with the green initiatives. This research is limited as urban hotels are surveyed in this study.
Originality/value
This work makes a valid argument to establish HCMI as a model initiative for environment quality improvement and further extension of other activities in the hospitality sector and scale-up sustainable practices for future-ready circular economies.