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Service triads refer to tripartite relationships in which client firms serve their customers through third-party service providers. The purpose of this paper is to systematically review the nascent but fast-growing literature on service triads to explore the broad themes along which the literature has grown, and to identify the gaps and future research opportunities.

Systematic literature review (SLR) approach is adopted to retrieve, select, and synthesise relevant service triads studies. A citation network analysis on the corpus resulting from the SLR identified the core articles of the literature.

The SLR uncovered ten themes of research along the articles’ objectives, theories and methodologies. The classification framework of service triads, the roles of customers and providers, the size of the provider, triadic risks, controlling service delivery and service quality, regulated triads, the stability of the triads, and cross-country, cross-culture triads emerged as significant under-researched areas.

The paper illustrates research trends and provides insights into the neglected and under-researched problems of service triads. This is the first SLR on service triads.

This review aims to give an overview about zinc oxide (ZnO) based gas sensors and the role of doping in enhancing the gas sensing properties. Gas sensors based on ZnO thin film are preferred for sensing applications because of their modifiable surface morphology, very large surface-to-volume ratio and superior stability due to better crystallinity. The gas detection mechanism involves surface reaction, in which the adsorption of gas molecules on the ZnO thin film affects its conductivity and reduces its electrical properties. One way to enhance the gas sensing properties is by doping ZnO with other elements. A few of the common and previously used dopants include tin (Sn), nickel (Ni) and gallium (Ga).

In this brief review, previous works on doped-ZnO formaldehyde sensing devices are presented and discussed.

Most devices provided good sensing performance with low detection limits. The reported operating temperatures were within the range of 200̊C –400̊C. The performance of the gas sensors can be improved by modifying their nanostructures and/or adding dopants.

As of yet, a specific review on formaldehyde gas sensors based on ZnO metal semiconductors has not been done.

Association rule mining generates the patterns and correlations from the database, which requires large scanning time, and the cost of computation associated with the generation of the rules is quite high. On the other hand, the candidate rules generated using the traditional association rules mining face a huge challenge in terms of time and space, and the process is lengthy. In order to tackle the issues of the existing methods and to render the privacy rules, the paper proposes the grid-based privacy association rule mining.

The primary intention of the research is to design and develop a distributed elephant herding optimization (EHO) for grid-based privacy association rule mining from the database. The proposed method of rule generation is processed as two steps: in the first step, the rules are generated using apriori algorithm, which is the effective association rule mining algorithm. In general, the extraction of the association rules from the input database is based on confidence and support that is replaced with new terms, such as probability-based confidence and holo-entropy. Thus, in the proposed model, the extraction of the association rules is based on probability-based confidence and holo-entropy. In the second step, the generated rules are given to the grid-based privacy rule mining, which produces privacy-dependent rules based on a novel optimization algorithm and grid-based fitness. The novel optimization algorithm is developed by integrating the distributed concept in EHO algorithm.

The experimentation of the method using the databases taken from the Frequent Itemset Mining Dataset Repository to prove the effectiveness of the distributed grid-based privacy association rule mining includes the retail, chess, T10I4D100K and T40I10D100K databases. The proposed method outperformed the existing methods through offering a higher degree of privacy and utility, and moreover, it is noted that the distributed nature of the association rule mining facilitates the parallel processing and generates the privacy rules without much computational burden. The rate of hiding capacity, the rate of information preservation and rate of the false rules generated for the proposed method are found to be 0.4468, 0.4488 and 0.0654, respectively, which is better compared with the existing rule mining methods.

Data mining is performed in a distributed manner through the grids that subdivide the input data, and the rules are framed using the apriori-based association mining, which is the modification of the standard apriori with the holo-entropy and probability-based confidence replacing the support and confidence in the standard apriori algorithm. The mined rules do not assure the privacy, and hence, the grid-based privacy rules are employed that utilize the adaptive elephant herding optimization (AEHO) for generating the privacy rules. The AEHO inherits the adaptive nature in the standard EHO, which renders the global optimal solution.

The purpose of this study is to explore circular economy (CE) initiatives and apply the stimulus-organism-response theory to find the socio-political drivers and enablers of CE in the pharmaceutical industry. CE as a concept was relatively not studied much with respect to socio-political interests from operations management perspectives. This was especially so in the pharmaceutical industry.

This research study was anchored in the theoretical conversation of stimulus-organism-response theory to find the socio-political interests and enablers of the regenerative CE principles. These were the functions of remanufacturing, reuse and recycle. For this research study, data was collected in two steps. First, eight industry practitioners were interviewed to understand the CE practices in the pharmaceutical industry. Then 166 chiefs of production and operations functions from 124 pharmaceutical companies were surveyed. The quantitative data was empirically analyzed using SmartPLS3 software.

This research study revealed that pressure from suppliers and other public stakeholders were driving regenerative CE practices in the pharmaceutical industry. The results further stated that CE enablers such as green information technology systems and internal environmental management were critical for making pharmaceutical manufacturing operations circular.

This research study measured the constructs on a formative scale. Studies measuring socio-political interests, CE enablers and sustainability practices constructs on a formative scale were much required for the development of the CE theory. This research study output could be applied across geographies and industries to measure the indicators of CE.

This research study indicated that in the context of the pharmaceutical industry, there was an overemphasis on the remanufacture and reuse principles. However, the focus on recycling principles was mostly subdued. For managers and regulators in the pharmaceutical sector, this research study provided clear insights that for more effective CE implementation. This was based on an effective application of recycling practices in the critical functions in pharmaceutical industry.

Earlier research studies on green and environmental manufacturing were focused on linear production models. To provide clear and robust foundations for CE theory, this research study considered operations management from the perspective of the value chain. This comprised the entire circular production model. Earlier research studies had treated socio-political interests, CE enablers and sustainability practices as reflective constructs. This study was one of the foremost to measure these constructs on a formative scale.

This study aims to develop and demonstrate a deposition framework for the implementation of a region-based adaptive slicing strategy for the Tungsten Inert Gas (TIG) welding-based additive manufacturing system. The present study demonstrates a deposition framework for implementing a novel region-based adaptive slicing strategy termed as Fast Interior and Accurate Exterior with Constant Layer Height (FIAECLH).

The mentioned framework has been developed by performing experiments using the design of experiments and analyzing the experimental data. Analysis results have been used to obtain the mathematical function to integrate customization in the process. The paper, in the end, demonstrates the FIAECLH framework for implementing region-based adaptive slicing strategy on the hardware level.

The study showcase a new way of implementing the region-based adaptive slicing strategy to arc-based metal additive manufacturing. The study articulating a new strategy for its implementation in all types of wire and arc additive manufacturing processes.

Wire-arc-based technology has the potential to deliver cost-effective solutions for metal additive manufacturing. The research on arc welding-based processes is being carried out in different dimensions. To deposit parts with complex geometry and better dimensional accuracy implementation of a novel region-based adaptive slicing strategy for the arc-based additive manufacturing process is an essential task. The successful implementation of an adaptive slicing strategy would ease the fabrication of complex geometry in less time. This paper accomplishes this need of implementing a region-based adaptive slicing strategy as no experimental investigation has been reported for the TIG-based additive manufacturing process.

Gives a bibliographical review of the finite element methods (FEMs) applied for the linear and nonlinear, static and dynamic analyses of basic structural elements from the theoretical as well as practical points of view. The range of applications of FEMs in this area is wide and cannot be presented in a single paper; therefore aims to give the reader an encyclopaedic view on the subject. The bibliography at the end of the paper contains 2,025 references to papers, conference proceedings and theses/dissertations dealing with the analysis of beams, columns, rods, bars, cables, discs, blades, shafts, membranes, plates and shells that were published in 1992‐1995.

This study presents the development of a supply chain (SC) observatory, which is a benchmarking solution to support companies within the same industry in understanding their positioning in terms of SC performance.

A case study is used to demonstrate the set-up of the observatory. Twelve experts on automatic equipment for the wrapping and packaging industry were asked to select a set of performance criteria taken from the literature and evaluate their importance for the chosen industry using multi-criteria decision-making (MCDM) techniques. To handle the high number of criteria without requiring a high amount of time-consuming effort from decision-makers (DMs), five subjective, parsimonious methods for criteria weighting are applied and compared.

A benchmarking methodology is presented and discussed, aimed at DMs in the considered industry. Ten companies were ranked with regard to SC performance. The ranking solution of the companies was on average robust since the general structure of the ranking was very similar for all five weighting methodologies, though simplified-analytic hierarchy process (AHP) was the method with the greatest ability to discriminate between the criteria of importance and was considered faster to carry out and more quickly understood by the decision-makers.

Developing an SC observatory usually requires managing a large number of alternatives and criteria. The developed methodology uses parsimonious weighting methods, providing DMs with an easy-to-use and time-saving tool. A future research step will be to complete the methodology by defining the minimum variation required for one or more criteria to reach a specific position in the ranking through the implementation of a post-fact analysis.

Graphene, which has abundant availability in nature, is currently under research for its functional applications in the field of textiles. The sp² Hybridized 1-atom-thick planar sheet has been under consideration for its unique electrical, mechanical and thermal properties, but there exists a void for aggregated data on the findings of other co-functional properties attained by the material using graphene oxide (GO) finish. This paper aims to define the techniques of extraction of GO, method of its application on textile material followed by detailed evaluation of the differential functional properties achieved.

The methodology used to explain the multiple functionalities of GO finish have been carried out by starting with the chemistry of graphene and the isolation of GO from graphite, followed by the techniques for its application on the textile along with the study on the induced functional properties that may aid to increase its potential applications.

It has been observed that with the aid of optimization of GO finish, the finish in lieu with the conductive potentialities may further provide with many essential properties such as hydrophobicity, ultraviolet protection and antibacterial property.

The field of research on GO finish is naive and except few properties, many functionalities are still unexplored that may enable its smooth production, handling and expanding its area of application. The agglomeration of scattered findings on the achievable functional properties of GO on various textiles has been achieved in this paper.

The purpose of this paper is to develop a statistical model for delamination and thrust forcing during drilling of carbon-fibre reinforced polymer (CFRP) composites using response surface methodology (RSM) to determine the input parameters (drill speed, drill diameter and feed rate) that influences the output response (delamination and thrust force) in the machining of CFRP composite using solid carbide drill cutter.

Three factors, three levels central composite face centred (CCFC) design, is used to conduct the experiments on CFRP by carbide drill. The whole quality evaluation (delamination) was done by video measuring system to measure the width of maximum damage of the machined CFRP composite. The thrust forces during drilling are measured using digital multi-component cutting force (Make: IEICOS, Model: 652) dynamometer. The “Design Expert 7.0” is used to analyse the data collected graphically. An analysis of variance is carried out to validate the model and for determining the most significant parameter.

The response surface model is used to predict the input factors influencing the delamination and thrust force on the drilled surfaces of CFRP composite at different cutting conditions with the chosen range of 95 per cent confidence intervals. The analysis on the influences of the entire individual input machining parameters on the delamination and thrust force has been carried out using RSM. This investigation revealed that the drill diameter is the eminent factor which affects the responses.

In all, 0.3, 0.4 and 0.5 mm holes have been successfully made on CFRP using vertical machining center, whereas the previous researchers have not drilled hole size less than 1 mm in CFRP using vertical machining center.