Joseph Vivek, Naveen Venkatesh S., Tapan K. Mahanta, Sugumaran V., M. Amarnath, Sangharatna M. Ramteke and Max Marian
This study aims to explore the integration of machine learning (ML) in tribology to optimize lubrication interval decisions, aiming to enhance equipment lifespan and operational…
Abstract
Purpose
This study aims to explore the integration of machine learning (ML) in tribology to optimize lubrication interval decisions, aiming to enhance equipment lifespan and operational efficiency through wear image analysis.
Design/methodology/approach
Using a data set of scanning electron microscopy images from an internal combustion engine, the authors used AlexNet as the feature extraction algorithm and the J48 decision tree algorithm for feature selection and compared 15 ML classifiers from the lazy-, Bayes and tree-based families.
Findings
From the analyzed ML classifiers, instance-based k-nearest neighbor emerged as the optimal algorithm with a 95% classification accuracy against testing data. This surpassed individually trained convolutional neural networks’ (CNNs) and closely approached ensemble deep learning (DL) techniques’ accuracy.
Originality/value
The proposed approach simplifies the process, enhances efficiency and improves interpretability compared to more complex CNNs and ensemble DL techniques.
Details
Keywords
Joseph Calandro and Vivek Paharia
The books, The Innovator’s Dilemma and Fooled by Randomness were best-sellers, and both books’ authors rightly have legions of followers. Nevertheless, the dynamics each author…
Abstract
Purpose
The books, The Innovator’s Dilemma and Fooled by Randomness were best-sellers, and both books’ authors rightly have legions of followers. Nevertheless, the dynamics each author analyzed so well continue to plague many executives. Why? Is there some way to close the analytical loop between these two extremes? Put another way, is there a practical method of being productive and profitable in “normal” environments while at the same time working to capitalize on the impact of volatile disruption? This paper presents a practical approach for doing so that builds on prior research.
Design/methodology/approach
This paper differentiates between the normal, linear environment of “business as usual” (BaU) and the volatile, nonlinear environments of disruption to both upside and the downside. It then profiles how to navigate each environment, illustrated by way of examples.
Findings
Our findings, which are supported by historical and contemporary examples, are that leading executives consistently navigate the environments of BaU and disruption due to explicit strategic decisions based on an “information advantage,” which is knowledge that their competitors either do not have or choose to ignore. Such advantages are monetized by efficient operations in BaU and by economically, which is to say strategically, benefiting from disruptive volatility to the upside and/or avoiding it on the downside, over time.
Practical implications
Managerial focus should be directed to potentially disruptive innovations and other kinds of ambiguous threats, which could develop to be strategically significant over time, and these need to be tracked in a meaningful way. To benefit from an information advantage, executives must selectively – that is, strategically – make small investments that could either payoff dynamically or economically mitigate the risk of extreme losses over time.
Originality/value
This paper offers executives a practical explanation why the environments of BaU and disruption must be analyzed and planned for separately by different functions. Doing so facilitates the efficient realization of corporate goals and objectives over time in both normal (linear) and highly volatile (nonlinear) environments.
Joseph Calandro Jr. and Vivek Paharia
This paper offers a practical overview of the U.S. credit cycle and the challenges it poses, along with a perspective on where we seem to be in the cycle in early 2023…
Abstract
Purpose
This paper offers a practical overview of the U.S. credit cycle and the challenges it poses, along with a perspective on where we seem to be in the cycle in early 2023. Suggestions are then offered for how corporate executives can address cyclical challenges from a corporate strategy perspective.
Design/methodology/approach
The United States credit cycle was out into context by following the trend of Moody’s Baa corporate bond yields from January 1919 to November 2022. Under the Moody’s rating system, Baa is the lowest level of investment grade credit, and as such it possesses speculative characteristics that are sensitive to cyclical dynamics. Another reason for choosing Baa credit patterns for analysis is data availability: over 100-years of continuous Baa data is searchable at the U.S. Federal Reserve.
Findings
The prior credit cycle wave of progressively lower inflation and interest rates began in 1982 and ended in 2020. The current credit cycle of wave of progressively higher inflation and interest rates will present strategic risks and opportunities that executives will increasingly have to deal with.
Originality/value
This is the first corporate strategy paper we are aware that practically addresses the credit cycle change. It is also the first paper we are aware that provides practical suggestions on how to address that change from a corporate strategy perspective.
Delonia O. Cooley and Vivek Madupu
This paper aims to investigate what sources of information consumers are utilizing when they are selecting physicians, and if there are any differences in the types of sources…
Abstract
Purpose
This paper aims to investigate what sources of information consumers are utilizing when they are selecting physicians, and if there are any differences in the types of sources they evaluate when searching for information for themselves versus searching for someone else (e.g. loved ones).
Design/methodology/approach
Focus groups and personal interviews were conducted based on a convenience sampling approach.
Findings
Consumers no longer depend on subjective sources such as word of mouth (WOM), but also look at objective internet sources. When searching for information for somebody else, consumers refer to more sources and prefer objective sources of information, such as the internet. When searching for loved ones, consumers spend more time and effort as they want to give the best possible advice.
Research limitations/implications
The study focused only on baby‐boomers. Hence, the results may not be extended to other segments. Hospitals and other not‐for‐profit groups providing health care information should make attempts to provide information about physicians' services on the internet. Health care marketers should recognize that searching for information for self versus searching for loved ones is not similar.
Originality/value
Health care marketers can begin investigating the necessary means of how consumers are searching for information for self versus searching for loved ones. They should put in place mechanisms to identify whether a consumer is searching for information for self or for somebody else. Consumers are now referring to the internet‐based information sources and not just WOM.
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Keywords
Sampath Kumar Ranganathan, Vivek Madupu, Sandipan Sen and John R. Brooks
The purpose of this study is to identity cognitive and affective determinants of customer loyalty towards e-mail services, including interrelationships, and to understand the…
Abstract
Purpose
The purpose of this study is to identity cognitive and affective determinants of customer loyalty towards e-mail services, including interrelationships, and to understand the process by which the cognitive and affective antecedents influence customer loyalty.
Design/methodology/approach
An online survey was conducted to gather data from Gmail users. Data were analyzed using structural equation modeling.
Findings
Results indicate electronic service quality and e-trust (cognitive) impact customer loyalty through affective variables like emotions, satisfaction, e-trust (affective) and affective commitment. Results also indicate that e-mail service providers who intend to build long term relationships with their customers will benefit by investing in emotional factors along with cognitive factors.
Research limitations/implications
A predominantly male audience responded to the research query based on one e-mail service setting. Based on the responses, it was determined that e-mail service providers can benefit by building emotional bonds with customers. Enhancing consumption emotions leads to development of emotional bonds and customer loyalty.
Originality/value
Much of the extant literature has examined the role played by cognitive antecedent variables in determining e-loyalty. Studies that researched the role of affective variables are scant. This paper is unique in that it examines both cognitive and affective variables in determining e-loyalty. This study differs from other studies in that it uses antecedents such as emotions, affective commitment, and e-trust (affective) to determine customer loyalty toward e-mail services. Interrelationships among the antecedents were also explored.