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The purpose of this paper is to benchmark and measure the comparative efficiency of emergency medical services (EMS) in major US cities (populations greater than 100,000). In so doing, this paper aims to develop a benchmark that can be emulated by cities lagging in EMS efficiency. Also, it seeks to develop a profile of cities that are successful in providing highly efficient EMS as benchmarks.

Data envelopment analysis is used to measure the EMS efficiency of 127 selected large cities in the USA under the premise of a constant‐return to scales method of service delivery. In addition, to identify factors influencing the US cities' EMS efficiency and then to predict their efficiency scores, a Tobit regression analysis is employed, which tended to result in a smaller standard error, a smaller bias, and a smaller mean squared error than ordinary least squares.

This paper examines whether more densely settled and populated areas have greater efficiency in delivering EMS. After controlling variables such as weather and climate, income, population growth, the age of a residential home, and geographic size of a city in land area, It is found that more densely settled, geographically large, and high income cities show more efficient provision of EMS.

This paper is the first to develop in a comprehensive way EMS benchmark performance standards for municipal governments and elaborate on a host of factors which are associated with the success of EMS deliveries. By setting such standards and identifying factors affecting EMS efficiency, this paper helps municipal governments to continuously improve their EMS and develop more efficient public policy.

The purpose of this paper is to unearth various dimensions of employee experience (EX) and explore how pandemic impacted various EX factors using online employee reviews. The authors identify employee-discussed EX-factors and quantify the associated sentiments and importance.

This paper employs Latent Dirichlet Allocation on the online employee reviews to identify the key EX-factors. The authors probe sentiments and importance associated with key EX-factors using sentiment analysis, importance analysis, regression analysis and dominance analysis.

The result of topic modeling identifies 20 EX-factors that shape overall EX. While skill development plays a major role in shaping overall EX, employees perceived Salary and Growth as the most important EX-factor and expressed negative sentiments during the pandemic. Employee sentiments significantly influence overall EX.

When employees have extensive change experience, managers should consider various facets of EX to manage the smooth change and deliver a better EX. This research offers key EX-factors to be considered by managers while dealing with employees. Online employee reviews websites are recommended to include the identified key EX-factors to comprehend the holistic EX.

This study contributes to the growing literature on the employee experience as a concept by identifying various EX-factors. The authors expand the extant EX scales by identifying an inclusive and updated set of EX-factors.

The game of cricket that originated in Britain thrives on passion and the following it generates in India and other South Asian countries is tremendous. The Board of Control for Cricket in India (BCCI) is the apex governing body that controls all cricketing events in the India. Being the richest such body, BCCI is the most powerful national body among similar organizations across countries where cricket is played. The world of cricket saw a sea change with the introduction of the Indian Premier League (IPL) due to its unprecedented commercial success. The case describes the betting scandal that hit IPL, BCCI and its promoter in the middle of 2013. The scandal involved the son-in-law of the President of BCCI. The events following the scandal saw the Supreme Court of India, the highest judicial body in the country, to indict BCCI and its President of serious misgovernance. Set in this backdrop, the case highlights governance issues in the functioning of not for profit organizations such as BCCI. The case provides an opportunity to reflect on and discuss as to how such quasi-public bodies ought to be governed.

Smart connected products (SCP) are the new archetype of products evolving. SCP are subtly changing the product-centric business to system-centric. Development and monetization of new SCP is an uphill task, it necessitates unique market orientation and business models. The purpose of this study is to establish a framework of variables influencing new smart connected products performance (NSCPP) at the market place, suggest methods to operationalize the framework.

The study identified key variables influencing NSCPP from existing literature. Conceptualized unique theoretical frameworks of these variables and empirically validated structural relationships. The study performed structural equation modeling using the data collected from 163 respondents having managed the development and monetization of 138 new SCP launches.

The study established structural relationships among selected variables proactive market orientation (ProMO), new product development proficiency (NPDPro) and business model innovation (BMoI). It revealed that the effect of ProMO is manifested through NPDPro. BMoI and NPDPro significantly influence NSCPP.

The study presented “ProMO Canvas” to plan and operationalize ProMO integrated with new product development (NPD) stage-gate activities. The study suggested the practitioners to execute ProMO activities preceding NPD activities and execute NPD, business model development activities in parallel to attain superior NSCPP.

This study is a novel effort to derive a unique empirical framework of variables ProMO, NPDPro and BMoI to attain superior NSCPP.

The purpose of this paper is to conduct an experimental investigation on the shock cell structure of jets emanating from a four-lobed corrugated nozzle using Schlieren imaging technique.

The Schlieren images were captured for seven different nozzle pressure ratios (NPR = 2, 3, 4, 5, 6, 7 and 8) and compared with the shock cell structure of a round nozzle with an identical exit area. The variation in the length of the shock cell, width of boundary interaction between adjacent shock cells, maximum width of first shock cell, Mach disk position and diameter for different NPR was measured from the Schlieren images and analysed.

A three-layer shock net observed in the jet emanating from the four-lobed corrugated nozzle is a novel concept in the field of under-expanded jet flows. A shock net represents interconnected layers of shock cells developed because of the interaction between the core and peripheral shock waves in a jet emanating from a corrugated lobed nozzle. Also, the pattern of shock net is different while taking Schlieren images across the groove and lobe sections. Thus, the shock net emerging from a corrugated lobed nozzle varies azimuthally and primarily depends on the nozzle exit cross section. The length of the shock cell, width of boundary interaction between adjacent shock cells, maximum width of first cell, Mach disk position and diameter were found to exhibit increasing trend with NPR.

A novel concept of interconnected layers of shock waves defined as “shock net” developed from a single jet emanating from a four-lobed corrugated nozzle was observed.

In a volatile agricultural postharvest market, producers require more personalized information about market dynamics for informed decisions on the marketed surplus. However, this adaptive strategy fails to benefit them if the selection of a computational price predictive model to disseminate information on the market outlook is not efficient, and the associated risk of perishability, and storage cost factor are not assumed against the seemingly favourable market behaviour. Consequently, the decision of whether to store or sell at the time of crop harvest is a perennial dilemma to solve. With the intent of addressing this challenge for agricultural producers, the study is focused on designing an agricultural decision support system (ADSS) to suggest a favourable marketing strategy to crop producers.

The present study is guided by an eclectic theoretical perspective from supply chain literature that included agency theory, transaction cost theory, organizational information processing theory and opportunity cost theory in revenue risk management. The paper models a structured iterative algorithmic framework that leverages the forecasting capacity of different time series and machine learning models, considering the effect of influencing factors on agricultural price movement for better forecasting predictability against market variability or dynamics. It also attempts to formulate an integrated risk management framework for effective sales planning decisions that factors in the associated costs of storage, rental and physical loss until the surplus is held for expected returns.

Empirical demonstration of the model was simulated on the dynamic markets of tomatoes, onions and potatoes in a north Indian region. The study results endorse that farmer-centric post-harvest information intelligence assists crop producers in the strategic sales planning of their produce, and also vigorously promotes that the effectiveness of decision making is contingent upon the selection of the best predictive model for every future market event.

As a policy implication, the proposed ADSS addresses the pressing need for a robust marketing support system for the socio-economic welfare of farming communities grappling with distress sales, and low remunerative returns.

Based on the extant literature studied, there is no such study that pays personalized attention to agricultural producers, enabling them to make a profitable sales decision against the volatile post-harvest market scenario. The present research is an attempt to fill that gap with the scope of addressing crop producer's ubiquitous dilemma of whether to sell or store at the time of harvesting. Besides, an eclectic and iterative style of predictive modelling has also a limited implication in the agricultural supply chain based on the literature; however, it is found to be a more efficient practice to function in a dynamic market outlook.

The purpose of this paper is to design and manufacture an intelligent 3D printed sensor to monitor the re-occurrence of diaphragmatic hernia (DH; after surgery) in bovines as an Internet of Things (IOT)-based solution.

The approach used in this study is based on a bibliographic analysis for the re-occurrence of DH in the bovine after surgery. Using SolidWorks and ANSYS, the computer-aided design model of the implant was 3D printed based on literature and discussions on surgical techniques with a veterinarian. To ensure the error-proof design, load test and strain–stress rate analyses with boundary distortion have been carried out for the implant sub-assembly.

An innovative IOT-based additive manufacturing solution has been presented for the construction of a mesh-type sensor (for the health monitoring of bovine after surgery).

An innovative mesh-type sensor has been fabricated by integration of metal and polymer 3D printing (comprising 17–4 precipitate hardened stainless steel and polyvinylidene fluoride-hydroxyapatite-chitosan) without sacrificing strength and specific absorption ratio value.

The purpose of this paper is to investigate returns to search (getting a better product and/or a lower price as a result of search) when consumers use/do not use recommendation agents (RAs). Specifically, it studies the effect of RAs/no RAs on decision quality, decision confidence and decision satisfaction taking into account subjective knowledge (SK) and involvement.

This paper employed two between-subjects factorial experimental designs with subjects searching for digital cameras in a simulated online digital camera store. The experiment was conducted with graduate students in Chennai, Bengaluru and Mysore in India.

Results of two online experiments showed that when consumers used RAs, low search led to better decision quality, whereas when consumers did not use RAs, medium search led to optimum decision quality. When consumers use RAs, SK had a U-shaped influence on the decision quality indicating that decision quality was the lowest for those with medium SK. When consumers did not use RAs, the effect of SK on decision quality was an inverted U-shape, indicating optimum decision quality for medium SK consumers. When consumers did not use RAs, subjects with high involvement made better choices, whereas when consumers used RAs, low involvement subjects made better choices. However, subjects who searched more had higher decision confidence and decision satisfaction even if their choices were not better.

The effect of RA vs no RA in conjunction with relevant consumer characteristics influencing decision quality of the consumer is demonstrated in this study. The findings have important managerial, consumer and theoretical contributions to make.

This paper aims to address the issue of gender inclusivity in the information technology (IT) sector of India. The main objective of the paper is to find out the factors influencing female participation in the IT industry. It proposes some policy initiatives to support involvement of women in adequate proportion in the workforce.

The study uses a unique set of data from 63 IT companies from three big cities of Delhi-National Capital Region (NCR), Bengaluru and Kolkata. An ordered logit model is applied to find out the determinants of female absorption in the IT industry. ANOVA is used to study the variations between and within the IT industry of female labor force participation.

Result reveals that the percentage and mobility of female employees in an organization does not depend on the turnover or the total number of skilled employees in the organization. It depends on the location.

The main limitation of the paper is that many IT companies do not want to reveal data about the percentage of female employees. If more companies could have been included, more accurate results could have been found.

The study discusses the aspect of gender inclusivity in the IT sector as well as the impact of higher skill on gender. The paper proposes some policy initiatives which can increase the number of female employees in the IT sector.

The study fulfills the need to know about the gender inclusivity aspect of the IT sector in India.

Dissimilar materials found applications in the structural fields to withstand the different types of loads and provide multi-facet properties to the final structure. Aluminum alloy materials are mostly used in aerospace and marine industries to provide better strength and safeguard the material from severe environmental conditions. The purpose of this study is to develop new material with superior strength to challenge the severe environmental conditions.

In the present investigation, friction stir welding (FSW) dissimilar joints were prepared from AA6061 and AA5083 aluminum alloys, and the weld nugget (WN) was reinforced with hard reinforcement particles such as La₂O₃ and CeO₂. The tribological and mechanical properties of the prepared materials were tested to analyze the suitability of material in the aerospace and marine environmental conditions.

The results showed that the AA6061–AA5083/La₂O₃ material exhibited better mechanical and tribological characteristics. The FSW dissimilar AA6061–AA5083/La₂O₃ material exhibited lower wear rate of 7.37 × 10⁻³ mm3/m and minimum friction coefficient of 0.31 compared to all other materials owing to the reinforcing effect of La₂O₃ particles and the fine grains formed by FSW process at WN region. Further, FSW dissimilar AA6061–AA5083/La₂O₃ material displayed a maximum tensile strength and hardness of 378 MPa and 118 HV, respectively, among all the other materials tested.

This work is original and novel in the field of materials science engineering focusing on tribological characteristics of friction stir welded dissimilar aluminum alloys by the reinforcing effect of hard particles such as La₂O₃ and CeO₂.