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The purpose of this paper is to describe the development of a personalised information support system to help faculty members to search various portals and e‐resources without typing the search terms in different interfaces and to obtain results re‐ordered without human intervention.

After a careful survey of various tools and techniques available for computerised client‐centred information services, the study selected to apply web usage mining, proxy level data collection and a vector space retrieval model to develop the personalised information support for teaching and research in a higher education institution.

There are practical constraints in the implementation stage. There is considerable difficulty in getting real and correct user interests and mapping them effectively into the products and services offered by the library. Also the interests of users change continuously. If multiple users share the same PC, it is difficult to identify the user as there is no one‐to‐one mapping between user and IP address.

The paper has not considered cases for all the faculty members due to time constraints. The results obtained from the system also need correlation with the sources actually used by the faculty to test its efficacy in a highly fluid research situation like higher academics.

A pragmatic client‐centred information support prototype described in this paper may find use in other institutions needing similar information support.

This paper demonstrates the pragmatic application of ICT for linking users and e‐resources in an academic library.

The aim of this paper is to study the effect of laser shock peening (LSP) on mechanical behaviour of the laser-directed energy deposition (LDED)-based printed 15-5 PH stainless steel with U and V notches. The study specifically concentrates on the evaluation of effect of scan strategy, machining and LSP processing on microstructural, texture evolution and fatigue behaviour of LDED-printed 15-5 PH steel.

For LSP treatment, 15-5 PH steel was printed using LDED process with bidirectional scanning strategy (XX [θ = 0°) and XY [θ = 90°]) at optimised laser power of 600 W with a scanning speed of 300 mm/min and a powder feed rate of 3 g/min. Furthermore, LSP treatment was conducted on the V- and U-notched fatigue specimens extracted from LDED-built samples at laser energy of 3.5 J with a pulse width of 10 ns using laser spot diameter of 3 mm. Post to the LSP treatment, the surface roughness, fatigue life assessment and microstructural evolution analysis is performed. For this, different advanced characterisation techniques are used, such as scanning electron microscopy attached with electron backscatter diffraction for microstructure and texture, X-ray diffraction for residual stress (RS) and structure information, Vicker’s hardness tester for microhardness and universal testing machine for low-cycle fatigue.

It is observed that both scanning strategies during the LDED printing of 15-5 PH steel and laser peening have played significant role in fatigue life. Specimens with the XY printing strategy shows higher fatigue life as compared to XX with both U- and V-notched conditions. Furthermore, machining and LSP treatment led to a significant improvement of fatigue life for both scanning strategies with U and V notches. The extent of increase in fatigue life for both XX and XY scanning strategy with V notch is found to be higher than U notch after LSP treatment, though without LSP samples with U notch have a higher fatigue life. As fabricated sample is found to have the lowest fatigue life as compared to machines and laser peened with both scan strategies.

This study presents an innovative method to improve the fatigue life of 15-5 PH stainless steel by changing the microstructure, texture and RS with the adoption of a suitable scanning strategy, machining and LSP treatment as post-processing. The combination of preferred microstructure and compressive RS in LDED-printed 15-5 PH stainless steel achieved with a synergy between microstructure and RS, which is responsible to improve the fatigue life. This can be adopted for the futuristic application of LDED-printed 15-5 PH stainless steel for different applications in aerospace and other industries.

The purpose of this paper is to review Lean Six Sigma (LSS) literature and report different definitions, demographics, methodologies and industries.

This paper highlights various definitions by different researchers and practitioners. A total of 235 research papers has been reviewed for the LSS theme, research methodology adopted, type of industry, author profile, country of research and year of publication.

From the review, four significant LSS classifications were identified that deal with the spread of LSS in different industries followed by observation for classification.

LSS is a strategy for success, but it did not examine its presence in various Industries. From this paper, readers can understand the quantum of its spread before implementing LSS. For academicians, it will be a comprehensive list of papers for research.

This paper reviews 235 research papers for their year, author profile, research methodology and type of industry. Various characteristics of LSS definitions and their theme are also reviewed.

The objective of this research work is to study the artificial intelligence (AI)-based product benefits and problems of the agritech industry. The research variables were developed from the existing review of literature connecting to AI-based benefits and problems, and 90 samples of primary data from agritech industry managers were gathered using a survey of a well-structured research questionnaire. The statistical package of IBM-SPSS 21 was utilized to analyze the data using the statistical techniques of descriptive and inferential statistical analysis. Results show that better information for faster decision-making has been ranked as the topmost AI benefit. This implies that the executives of agritech units have a concern about the quality of decisions they make and resistance to change from employees and internal culture has been ranked as the topmost AI problem.

The effect of increasing lip thickness (LT) and Mach number on subsonic co-flowing Jet (CFJ) decay at subsonic and correctly expanded sonic Mach numbers has been analysed experimentally and numerically in this study. This study aims to a critical LT below which mixing enhances and above which mixing inhibits.

LT is the distance, separating the primary nozzle and the secondary duct, present in the co-flowing nozzle. The CFJ with LT ranging from 2 mm to 150 mm at jet exit Mach numbers of 0.6, 0.8 and 1.0 were studied in detail. The CFJ with 2 mm LT is used for comparison. Centreline total pressure decay, centreline static pressure decay and near field flow behaviour were analysed.

The result shows that the mixing enhances until a critical limit and a further increase in the LT does not show any variation in the jet mixing. Beyond this critical limit, the secondary jet has a detrimental effect on the primary jet, which deteriorates the process of mixing. The CFJ within the critical limit experiences a significantly higher mixing. The effect of the increase in the Mach number has marginal variation in the total pressure and significant variation in static pressure along the jet axis.

In this study, the velocity ratio (VR) is maintained constant and the bypass ratio (BR) was varied from low value to very high values for subsonic and correctly expanded sonic. Presently, commercial aircraft engine operates under these Mach numbers and low to ultra-high BR. Hence, the present study becomes essential.

This is the first effort to find the critical value of LT for a constant VR for a Mach number range of 0.6 to 1.0, compressible CFJ. The CFJs with constant VR of unity and varying LT, in these Mach number range, have not been studied in the past.

This paper aims to develop supply chain strategies for the fashion retail supply chain (FRSC), likely to be disrupted by the current pandemic (COVID-19) under physical and online retail stores. The resilient retail supply chain design is proposed under budget allocation and merchandise capacity constraints.

This paper utilises the theory of constraint (ToC) and goal programming (GP) to address the COVID-19 impact on FRSC. The budgetary and capacity constraints are formulated with a constraint optimisation model and tested with six different priorities to deal with the physical and online stores. Next, all priorities are developed under different FRSC business scenarios. The ToC-GP-based optimisation model is validated with one of the Indian fashion retail supply chains.

The proposed optimisation model presents the optimal retailing strategies for selling fashion goods over physical and online platforms. The multiple scenarios are presented for developing trade-offs among different strategies to maximise the retailer's merchandise performance. This paper also highlighted the strategic movement from high merchandise density stores to low merchandise density stores. This implies a reduction of sales targets and aspiration levels of both online and physical fashion stores.

The proposed model is validated with one of the fashion retailers in India. Other nations or multiple fashion retailers might be considered for more generalisation of findings in the future.

This research helps fashion retail supply chain managers deal with consumer demand uncertainty over physical and online stores in pandemic times. Limitation: Other nations or multiple fashion retailers might be considered for more generalisation of findings in the future.

This is the first study that considered the impact of COVID-19 on the retail fashion supply chain. The effect of physical and online platforms is mainly discussed from consumer marketing perspectives, but an inventory and resilience perspective is missing in earlier studies. The role of merchandise planning is highlighted in this study.

This study aims to understand the influence of R&D intensity and ownership concentration on performance of Indian technology SMEs, at the intersection of “value creation” perspective of corporate governance and country cultural context in innovation.

Cross-sectional data of 264 Indian technology SMEs have been employed to probe the impact of ownership and R&D intensity on market performance of the technology SMEs.

This study does not find support of individual influence of R&D intensity on SME performance. The authors find support for the “value creation” hypothesis of corporate governance in Indian technology SME context. This study finds that interaction of promoter's ownership concentration and R&D intensity has a positive influence on the performance of Indian technology SMEs.

This study has deployed cross-sectional data. Future studies can examine the “value creation” hypothesis based on panel data for a long-run understanding. Ownership can be further segregated into different categories of ownership in future studies.

This study underscores on distinct necessity in the concentrated ownership in the context of Indian technology SMEs. The findings of the study may encourage policymakers to focus on the “value creation” of the technology SMEs than “value protection.”

This study aims to understand the market value of R&D practice of SMEs. The findings of this study establish that R&D intensity individually may not have any significant influence on SME performance. R&D intensity coupled with concentrated ownership can significantly increase SME performance. Thus, this study identifies factors that can help in SME innovation and growth options. Additionally, this study advocates for the fact concentrated ownership in technology SMEs of India by establishing the link with SME performance.

This study aims to identify, analyze and rank the critical success factors (CSFs) of Lean Six Sigma (LSS) implementation in Indian manufacturing sector based micro, small and medium enterprises (MSMEs). This study provides critical insight for managers and researchers aspiring for successful implementation of LSS in Indian manufacturing MSMEs.

The CSFs were extracted from literature followed by a questionnaire-based survey from 120 industry professionals with extensive knowledge and experience about LSS working in Indian manufacturing MSMEs. Further, the CSFs were grouped based on their fundamental relevance and ranked using best worst method (BWM) approach using inputs from LSS experts.

This study provides insights on success factors that have helped Indian manufacturing MSMEs to implement LSS. The findings signify that “Strategy based CSFs” were ranked as the top most important factors, followed by two other category factors namely “Bottom-Line CSFs” and “Supplier based and other category-based CSFs”.

The proposed research is specifically relevant to the context of MSMEs in the Indian manufacturing sector. In the future, the same approach can be extended to a global context, encompassing service sector-based MSMEs in healthcare and finance.

This study provides valuable inputs for managers, decision-makers, industrial practitioners and researchers about Indian manufacturing MSMEs. The identified CSFs and their prioritization offer a roadmap for successful adoption of LSS. Managers can allocate resources, and make strategic decisions based on the prioritized CSFs. Decision-makers can align their initiatives with the identified CSFs. Industrial practitioners gain insights to enhance their LSS initiatives, and researchers can focus their efforts on areas critical to LSS implementation in Indian MSMEs. Furthermore, the structured approach employed in this study can be adopted by various MSME sectors globally, thereby broadening the comprehension of LSS implementation.

This study contributes to the existing body of knowledge by addressing the gaps in literature on CSFs related to LSS adoption within Indian manufacturing MSMEs. While LSS has been widely studied, there is limited focus on its adoption in the context of Indian MSMEs. The combination of extensive literature review, questionnaire-based survey and the application of the BWM approach for prioritizing CSFs adds originality to the research.

Many organizations have reported significant benefits after the implementation of Lean Six Sigma (LSS). Embracing LSS requires asking some important questions: How Lean Six Sigma Readiness (LESIRE) can be measured? How can an organization identify the barriers for LESIRE? Answers to these questions are critical to both academicians and practitioners. The paper aims to discuss this issue.

This study illustrates the development process of a Lean Six Sigma Readiness (LESIRE) evaluation model to assess an organization’s readiness for LSS deployment using the fuzzy approach. The model was developed from 4 enablers, 16 criteria and 46 attributes of LSS, identified through a literature review.

To demonstrate the efficiency of the model, this study testing the LESIRE evaluation model in three Indian SMEs. Using experts’ ratings and weight, the researchers calculated the Fuzzy Lean Six Sigma index (FLSS) which indicates the LESIRE level of an organization and the Fuzzy Performance Importance Index (FPII) that helps to identify the barriers for LESIRE.

The main limitations of this study are that it did not consider the failure factors of LSS for model development and the LESIRE was only tested in manufacturing industries. Thus, future researchers could focus on developing a model with failure factors. The results obtained from the SMEs show that LESIRE is capable of assessing LESIRE in an industrial scenario and helps practitioners to measure LESIRE for the future decision making process.

The LESIRE model is easy to understand and use without much computation complexity. This simplicity makes the LESIRE evaluation model unique from other LSS models. Further, LESIRE was tested in three different SMEs, and it aided them to identify and improve their weak areas, thereby readying them for LSS deployment.

The main contribution of this study it proposes a LESIRE model that evaluates the organization for FLSS and FPII for LESIRE, which is essential for the organization embarking on an LSS journey. Further, it improves the readiness of the organization that is already practicing LSS.