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The paper explores and characterizes antifragility in simple inventory systems exposed to demand variability, providing the initial inroads to operationalizing antifragility in the context of inventory management. Antifragility refers to the feature of a system that can benefit from uncertainty, rather than suffer from it. The paper expands the concept of inventory beyond that of risk mitigation and towards one of enabling antifragility.

The study employs analytical and simulation modelling of an inventory system with two classes of demand. To separate the influence of factors, a simple inventory policy with a range of fixed order quantities is modelled, allowing for the identification of antifragile regions in an experimental space.

Outputs uncover a variety of performance outcomes, ranging from settings where additional inventory yields no benefit, to areas where additional inventory results in increasing normalized profit with increasing uncertainty, demonstrating antifragility. In between these regions, increases in normalized profit are bounded, and confined to specific regions.

This research expands academic understanding of inventory as a vehicle to achieving antifragile outcomes. Although this paper does not solve for an optimal policy as typical inventory research does, it instead characterizes the antifragile outcomes within simple inventory systems. Further research should be carried out to investigate antifragility in settings of greater complexity and design ordering policies leveraging inventory towards a gain from uncertainty.

Typically, inventory is used to buffer against uncertainty, and, with a given amount of inventory, the performance is expected to degrade with increasing variability. In this paper, the authors demonstrate that certain levels of additional inventory can result in antifragility and increase profitability as uncertainty increases, extending beyond traditional conceptualizations of inventory and uncertainty.

Empirical research into designing antifragile outcomes is limited, with very few examples of increasing performance with increases in uncertainty. This article presents an initial empirical exploration of how additional inventory can result in antifragility.

During drilling in coal mines, sticking of drill rod (referred to as SDR in this work) is a potential threat to underground safety. However, no practical measures to deter SDR have been developed yet. The purpose of this study is to develop an anti-SDR strategy using proportional-integral-derivative (PID) and compliance control (PIDC). The proposed strategy is compatible with the drilling process currently used in underground coal mines using drill rigs. Therefore, this study aims to contribute to the PIDC strategy for solving SDR.

A hydraulic circuit to reduce SDR was built based on a load-independent flow distribution system, a PID controller was designed to control the inlet hydraulic pressure of the rotation motor and a typical compliance control approach was adopted to control the feed force and displacement. Moreover, the weight and optimal combination of the alternative admittance control parameters for the feed cylinder were obtained by adopting the orthogonal experiment approach. Furthermore, a fuzzy admittance control approach was proposed to control the feed displacement. Experiments were conducted to test the effectiveness of the proposed method.

The experimental results indicated that the PIDC strategy was appropriate and effective for controlling the rotation motor and feed cylinder; thus, the proposed method significantly reduces the SDR during drilling operations in underground coal mines.

As the PIDC strategy solves the SDR problem in underground coal mines, it greatly improves the safety of coal mine operation and decreases the power cost. Consequently, it brings the considerable benefits of coal mine production and vast application prospects in other corresponding fields. Actual drilling conditions are difficult to accurately simulate in a laboratory; thus, for future work, drilling experiments can be conducted in actual underground coal mines.

The PIDC-based anti-SDR strategy proposed in this study satisfactorily controls the rotation motor and feed cylinder and facilitates the feed and rotation movements. Furthermore, the tangible novelty of this study results is that it improves the frequency response of the entire drilling system. The drilling process with PIDC decreased the occurrence of SDR by 50%; therefore, the anti-SDR strategy can significantly improve the safety and efficiency of underground coal mining.

This study aims to understand how informational factors influence online purchase intention when considering secondhand books.

A conceptual model linking book condition, description, delivery cost, picture, sellers’ rating and delivery date to purchase intention was developed and tested by using structural equation modeling. Survey data from 234 respondents was used to analyze both direct and mediating relationships.

The examination demonstrates how book condition, delivery cost and sellers’ rating influence consumers’ purchase intention. Book condition directly and indirectly influenced purchase intention, while delivery cost and sellers’ rating were significant only when including the mediating variable delivery date.

This work clarifies where resources should be allocated when offering secondhand books online. Sellers should dedicate time to include informational factors such as book condition, delivery cost and sellers’ rating. Contra wise, there is little value expounding on the book’s description or providing a high-quality picture when selling online.

This paper adopts a modified Taguchi approach to develop empirical relationships to the performance characteristics (output responses) in terms of process variables and demonstrated their validity through comparison of test data. The method suggests a few tests as per the orthogonal array and provides complete information for all combinations of levels and process variables. This method also provides the estimated range of output responses so that the scatter in the repeated tests can be assessed prior to the tests.

In order to obtain defect-free products meeting the required specifications, researchers have conducted extensive experiments using powder bed fusion (PBF) process measuring the performance indicators (namely, relative density, surface roughness and hardness) to specify a set of printing parameters (namely, laser power, scanning speed and hatch spacing). A simple and reliable multi-objective optimization method is considered in this paper for specifying a set of optimal process parameters with SS316 L powder. It was reported that test samples printed even with optimal set of input variables revealed irregular shaped, microscopic porosities and improper melt pool formation.

Finally, based on detailed analysis, it is concluded that it is impossible to express the performance indicators, explicitly in terms of equivalent energy density (E_0ˆ*), which is a combination of multiple sets of selective laser melting (SLM) process parameters, with different performance indicators. Empirical relations for the performance indicators are developed in terms of SLM process parameters. Test data are within/close to the expected range.

Based on extensive analysis of the SS316 L data using modified Taguchi approach, the optimized process parameters are laser power = 298 W, scanning speed = 900 mm/s and hatch distance = 0.075 mm, for which the results of surface roughness = 2.77 Ra, relative density = 99.24%, hardness = 334 Hv and equivalent energy density is 4.062. The estimated data for the same are surface roughness is 3.733 Ra, relative density is 99.926%, hardness is 213.64 Hv and equivalent energy density is 3.677.

Even though equivalent energy density represents the energy input to the process, the findings of this paper conclude that energy density should no longer be considered as a dependent process parameter, as it provides multiple results for the specified energy density. This aspect has been successfully demonstrated in this paper using test data.

This study aims to investigate the conditions for the financial feasibility of an incentive-based model for self-drop or crowdsourced drop of the product to be returned at designated drop boxes (thereby ensuring a contactless process).

Constraint-based non-linear mathematical modeling was done for cost differential with and without crowdsourcing. This was analyzed against returns on investment for the installed infrastructure. Scenarios were looked into from the linear, iso-elastic and logarithmic demand functions to identify the optimal incentive policy. The results were further evaluated using “willingness to return” for customer willingness for product returns via drop boxes.

Crowdsourcing is viable when product returns are no more than 15%–20% of the overall products, with a logistics cost differential of 15%–25%. These were only viable when the product return incentive was within the range of 15%–20% of the product cost, as well as the penalty was in the range of 25 to 40% for wrong returns.

The findings are expected to aid the organizations in successfully designing product return policies while adhering to the post-COVID-19 norms, including contactless transactions and social distancing.

The study provides a look into the viability sensitivity of effective gains/profitability against the required level of service for returns, wrong returns, penalties and incentives for crowdsourcing in a developing country like India.

The case study has been prepared for management students/business executives to understand electric vehicle (EV) business, business environment, industry competition and strategic planning and strategy implementation.

The size of the Indian passenger vehicle market was valued at US$32.70bn in 2021; it was projected to touch US$54.84bn by 2027 with a Compound Annual Growth Rate (CAGR) of more than 9% during the period 2022–2027. The passenger vehicle industry, a part of the overall automotive industry, was expected to grow at a rapid pace, as the Indian economy was rising at the fastest rate. However, the Government of India (GoI) had put a condition on the growth scenario by mandating that 100% of vehicles produced would be EVs by 2030. Tata Motors (TaMo), a domestic player in the market, had been facing a challenging competitive environment. Although it had been incurring losses, it had successfully ventured into the EV business. TaMo had taken advantage of the first mover by creating an electric mobility business vertical to enable the company to deliver on its aspiration of providing innovative and competitive e-mobility solutions. TaMo leadership had been putting efforts to scale up the electric mobility business, thus, contributing to GoI’s plan for electric mobility. Shailesh Chandra, president of electric mobility business, had a big task in hand. He had to scale up EV production and sales despite insufficient infrastructure for charging and shortages of electronic components for manufacturing.

The case study has been prepared for management students/business executives for strategic management class. It is recommended that the case study is distributed in advance so that the students can prepare well in advance for classroom discussions. Groups will be created to delve into details for a specific question. While one group will make their presentation, the other groups will question the solution provided and give suggestions.

Teaching notes are available for educators only.

CSS 11: Strategy.

Conventional sportswear design does not take into account body size changes that many individuals experience (e.g. through pregnancy, puberty, menstruation, etc.). This paper aims to detail both the construction of a novel wearable shape-adaptive composite and a new meso-scale material design method, which enables the optimal creation of these structures.

This work reports the development of a predictive computational model and a corresponding design tool, including results of a tensile testing protocol to validate their outputs. A mathematical model was developed to explore the geometric parameter space of a bi-stable composite system, which then feeds into an optimization design tool.

The authors found that it is possible to fabricate shape-adaptive composites via 3D printing bi-stable structures, and adhering them to a base textile. Experimental mechanical tensile testing showed good agreement with the predictive model in mid-range unit cell amplitude designs. To illustrate how the optimization design tool works this paper details two design examples, one for expected shape change during pregnancy and one for targeted compression for high performance swimwear. The optimized design parameters are shown to replicate the target parameters, however there is potential for further improvement with a lower stiffness base textile.

Although there is a wealth of research on multi-stable mechanisms, there is a dearth of studies that apply these structures in the wearable composite space. Additionally, there is a need for design methods which leverage the structurally-programmable capabilities of multi-stable structures to create optimized, high-performance functional composites.

This study shows the influence of consumers' goal and strategy of maximization on the process behind their behavioral response to price.

Data was collected through a 2×2 experimental design involving 314 respondents and analyzed using PLS-SEM.

The results show that when buyers maximize, their transaction value and acquisition value perceptions predict their behavioral response to deals and discounts. Further, these buyers do not consider sales price information to form their internal reference price. On the other hand, when buyers satisfice, their transaction value perceptions predict the behavioral responses to price deals, and the relationship between transaction value and the behavioral response is not mediated by acquisition value. Further, such buyers consider sales price to form their internal reference price.

The theory of purchase value assumes that consumers seek to maximize their value. Our work relaxes this assumption to show how value maximizers (and satisficers) differ in the process of value formation and their responses to price promotions.

This paper aims to highlight a broader definition of good building performance that goes beyond the traditional emphasis on technical aspects, only adopting the lens of the social construction of technology (SCOT) in the empirical space of the workplace sector. Several building performance evaluation (BPE) methods focus on technical aspects such as energy consumption, indoor environmental conditions and compliance with building regulations and standards. Technical aspects, albeit important goals, only embed a partial component of what buildings are expected to deliver. There is growing interest in considering the organisational and experiential expectations of building performance, particularly integrating various views of performance as expected by different user groups.

The paper adopts an archival research method to analyse the archive of the workplace consultants DEGW, particularly focusing on their work on London’s Broadgate development in the 1980s and the 1990s.

The findings reveal how voices from a pluralistic client organisation can be addressed to articulate a broad definition of building performance that integrates different viewpoints encompassing technical, organisational and experiential expectations. In DEGW’s work, the views on building performance of various stakeholders involved in the everyday use and management of buildings are identified without imposing predetermined agendas or research notions of performance. Particular emphasis is given to understanding clients as not a homogenous entity but consisting of different interest groups, which implies multiple conceptualisations of building performance and the building itself.

The performance expectations of a building vary between organisations and even within any organisation. Moreover, the needs of an organisation will change over time, and the BPE criteria need to be changed to ensure better alignment between organisations and the physical spaces they occupy. A critical reflection on the conceptualisation of “users” and “building” in BPE methods is required to create an integrated approach towards building performance.

The paper offers insights by adopting the theoretical lens of SCOT to explore an integrated approach to building performance that captures the varied needs of building users through the example of London’s Broadgate development.

This study aims to focus on verifying the possibility of monitoring the condition of a turboprop engine using data recorded by on-board avionics Garmin G1000. This approach has potential benefits for operators without the need to invest in specialised equipment. The main focus was on the inter-turbine temperature (ITT). An unexpected increase in temperature above the usual value may indicate an issue with the engine. The problem lies in the detection of small deviations when the absolute value of the ITT is affected by several external variables.

The ITT is monitored by engine sensors and stored by avionics 1× per second onto an SD card. This process generates large amount of data that needs to be processed. Therefore, an algorithm was created to detect the steady states of the engine parameters. The ITT value also depends on the flight parameters and surrounding environment. As a solution to these effects, the division of data into clusters that represent the usual flight profiles was tested. This ensures a comparison at comparable ambient pressures. The dominant environmental influence then remain at the ambient air temperature (OAT). Three OAT compensation methods were tested in this study. Compensation for the standard atmosphere, compensation for the standard temperature of the given flight level and compensation for the speed of the generator, where the regression analysis proved the dependence between the ambient temperature and the speed of the generator.

The influence of ambient temperature on the corrected ITT values is noticeable. The best method for correcting the OAT appears to be the use of compensation through the revolutions of the compressor turbine NG. The speed of the generator depends on several parameters, and can refine the corrected ITT value. During the long-term follow-up, the ITT differences (delta values) were within the expected range. The tested data did not include the behaviour of the engine with a malfunction or other damage that would clearly verify this approach. Therefore, the engine monitoring will continue.

This study presents a possible approach to turbine engine condition monitoring using limited on board avionic data. These findings can support the development of an engine condition monitoring system with automatic abnormality detection and low operating costs.

This article represent a practical description of problems in monitoring the condition of a turboprop engine in an aircraft with variable flight profiles. The authors are not aware of a similar method that uses monitoring of engine parameters at defined flight levels. Described findings should limit the influence of ambient air pressure on engine parameters.