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This paper examines Aman Ullah’s contributions to robust inference, finite sample econometrics, nonparametrics and semiparametrics, and panel and spatial models. His early works on robust inference and finite sample theory were mostly motivated by his thesis advisor, Professor Anirudh Lal Nagar. They eventually led to his most original rethinking of many statistics and econometrics models that developed into the monograph Finite Sample Econometrics published in 2004. His desire to relax distributional and functional-form assumptions lead him in the direction of nonparametric estimation and he summarized his views in his most influential textbook Nonparametric Econometrics (with Adrian Pagan) published in 1999 that has influenced a whole generation of econometricians. His innovative contributions in the areas of seemingly unrelated regressions, parametric, semiparametric and nonparametric panel data models, and spatial models have also inspired a larger literature on nonparametric and semiparametric estimation and inference and spurred on research in robust estimation and inference in these and related areas.

This paper aims to propose an efficient artificial neural network (ANN) model using multi-layer perceptron philosophy to predict the fireside corrosion rate of superheater tubes in coal fire boiler assembly using operational data of an Indian typical thermal power plant.

An efficient gradient-based network training algorithm has been used to minimize the network training errors. The input parameters comprise of coal chemistry, namely, coal ash and sulfur contents, flue gas temperature, SOX concentrations in flue gas, fly ash chemistry (Wt.% Na₂O and K₂O).

Effects of coal ash and sulfur contents, Wt.% of Na₂O and K₂O in fly ash and operating variables such as flue gas temperature and percentage excess air intake for coal combustion on the fireside corrosion behavior of superheater boiler tubes have been computationally investigated and parametric sensitivity analysis has been undertaken.

Quite good agreement between ANN model predictions and the measured values of fireside corrosion rate has been observed which is corroborated by the regression fit between these values.

The aim of this paper is to study the effect of the parametric sensitivity of all critical parameters of feed water and other operating variables on the corrosion rate and oxide scale deposition on economizer tubes of a typical coal-fired 250-MW boiler.

In this paper, a multilayer perceptron-based artificial neural network (ANN) model has been developed to envisage the corrosion rate and oxide scale deposition rate in economizer tubes of a coal-fired boiler. The neural network architecture has been optimized using an efficient gradient-based network optimization algorithm to minimize the training and testing errors rapidly during simulation runs.

The parametric sensitivity of all critical parameters of feed water and other operating variables on the corrosion rate and oxide scale deposition activities has been investigated. It has been observed that dissolved oxygen, dissolved copper content, residual hydrazine content and pH of the feed water have a relatively predominant influence on the corrosion rate, whereas dissolved iron content, silica content, pH and temperature of the feed water have a moderately major influence on oxide scale deposition phenomenon. There has been very good agreement between ANN model predictions and the measured values of corrosion rate and oxide scale deposition rate substantiated by the regression fit between these values.

This paper details the development of an alternative model to accurately predict corrosion rate and deposition rate on the inner surface of economizer tubes of a boiler over first principle-based kinetic model.

Recent public policy initiatives seek greater transparency in financial reporting through an honest, balanced and thorough management discussion of company performance in the annual report. Management’s discussion invariably includes key performance indicators, such as financial ratios, relevant to external stakeholders. We model the impact of accounting estimates, assumptions, choices and errors on the risk of misleading financial ratios. This framework is illustrated through good and bad examples of financial reporting practices and by simulation of financial data of public companies. We provide a structured approach to inform policymakers, auditors and other stakeholders of the incremental financial reporting risk that accompanies current regulatory efforts.

The present study uses dynamic capabilities and micro foundations theory to unearth the emergence of multilevel innovation in service sector organizations. Transformational leadership (TL) and corporate social responsibility (CSR) are proposed as human resource (HR) based antecedents. The study also aims to reveal the role of collective organizational engagement (COE) as a mediator in developing dynamic capabilities and contingent pay policy (CPP) as a moderator.

The research is a multilevel study where employees are nested within organizations. We used multilevel modeling in Mplus V. 8.7 to perform the analyses.

Results of multilevel structural equation modeling revealed that TL, CSR, and COE are vital microfoundations through which innovation emerges in an organization. COE acts as a partial mediator in the relationship between CSR and innovation. The level of CPP in organizations moderates these relationships at the employee level rather than at the firm level.

This research is one of the few multilevel and multisource studies to empirically test the impact of HR-based antecedents on innovative work behavior and firm innovativeness simultaneously. It also contributes to engagement literature by furthering an understanding of the nascent concept of COE.

The advances and continuous development of technology have been identified as significant influences on the accounting profession (AICPA, 1998). In the last twenty years, both academia and the accounting profession have been giving much attention to the demand and opportunity for audits to be performed automatically, continuously and in nearly real time. This paper presents a comprehensive review of continuous auditing research by providing an overview of the emergence and growth of the continuous auditing literature and classifying the extant continuous auditing research on the basis of four research characteristics indicated by a newly developed research taxonomy.

The purpose of this study is to advance the understanding of resource orchestration in inter-firm partnerships that appropriately configure and align strategic cross-firm supply chain resources and capabilities generating synergies to deliver superior performance.

Applying the resource orchestration logic, supported by the relational view of competitive advantage, the study draws from an empirical analysis of survey data from 152 top-level executives of US manufacturing firms to investigate the effect of leveraging and coherently combining cross-firm supply chain resources with capabilities on operational performance.

The study underscores the view that appropriately orchestrated combinations of key partnership resources and capabilities as mechanisms for marketing strategy implementation, enhance performance. Specifically, research results suggest that complementary inter-firm resources and lean align, and similarly idiosyncratic resources and agility align synergistically to deliver superior operational performance outcomes. The results also accent partnership responses to intense competition, enabling enhanced operational performance. The findings thus enrich the understanding of the resource orchestration logic and strategy, making important theoretical contributions.

As is typical in marketing and strategy research, the study research design has a cross-sectional framework, thus limiting insights on the resource orchestration dynamics that can otherwise be generated using a longitudinal design. Also, the resource orchestration stream is still nascent. Further research is needed to delineate the orchestration mechanisms that deliver on performance outcomes, especially in supply chains.

A key insight for supply chain and marketing managers is that close-knit inter-firm partnerships are critical for accessing idiosyncratic and complementary resources that can be configured and symbiotically aligned with market-facing agility and lean capabilities, respectively, to deliver market value. Proactive partnerships, especially in highly competitive and disruptive environments, enable mobilizing cross-firm resources and building appropriate matching combinations with capabilities to deliver on operational performance.

The study, guided by theory, advances the understanding of how key cross-firm resources and capabilities deliver performance gains. The key to competitive advantage and enhanced performance outcomes may lie in acquiring, leveraging and deploying appropriately matched resource-capability combinations. The present study investigates this proposition within the context of supply chain partnerships, focusing on cross-firm resources and capabilities.

India has a distinct family hierarchy and a vertical collectivistic culture. Indian traditional cultural norms discourage young adults from having romantic or sexual relationships before marriage. Romantic liaisons and marriages are fiercely opposed outside the caste and social network. Despite this cultural practice, research in the last decade demonstrated that more young adults in India engage in premarital romantic relationships and prefer a marriage of choice. However, they strongly wish their parents to approve of their partner and arrange their marriage. This increasing trend of love-cum-arranged marriages could be considered how Indian culture adapts to the demands of modernization strongly impelled by globalization. This chapter discusses the dynamics of change in the romantic and marital agency among young adults in India. First, the authors provide a brief historical introduction to the Indian marital system. Then, the authors discuss the changing cultural dimensions that promote marital choice and independence in partner selection (e.g., filial piety). Further, the authors provide an overview of the trends in premarital romantic relationships in India. In addition, the authors discuss the distress and conflict in Indian families due to the increasing premarital romantic and sexual relationships among Indian youth, as evidenced by eloped marriages, forced marriages, and honor killings.

The advances and continuous development of technology have been identified as significant influences on the accounting profession (AICPA, 1998). In the last twenty years, both academia and the accounting profession have been giving much attention to the demand and opportunity for audits to be performed automatically, continuously and in nearly real time. This paper presents a comprehensive review of continuous auditing research by providing an overview of the emergence and growth of the continuous auditing literature and classifying the extant continuous auditing research on the basis of four research characteristics indicated by a newly developed research taxonomy.

The Web is the largest repository of information. Personal information is usually scattered on various pages of different websites. Search engines have made it easier to find personal information. An attacker may collect a user's scattered information together via search engines, and infer some privacy information. The authors call this kind of privacy attack “Privacy Inference Attack via Search Engines”. The purpose of this paper is to provide a user‐side automatic detection service for detecting the privacy leakage before publishing personal information.

In this paper, the authors propose a user‐side automatic detection service. In the user‐side service, the authors construct a user information correlation (UICA) graph to model the association between user information returned by search engines. The privacy inference attack is mapped into a decision problem of searching a privacy inferring path with the maximal probability in the UICA graph and it is proved that it is a nondeterministic polynomial time (NP)‐complete problem by a two‐step reduction. A Privacy Leakage Detection Probability (PLD‐Probability) algorithm is proposed to find the privacy inferring path: it combines two significant factors which can influence the vertexes' probability in the UICA graph and uses greedy algorithm to find the privacy inferring path.

The authors reveal that privacy inferring attack via search engines is very serious in real life. In this paper, a user‐side automatic detection service is proposed to detect the risk of privacy inferring. The authors make three kinds of experiments to evaluate the seriousness of privacy leakage problem and the performance of methods proposed in this paper. The results show that the algorithm for the service is reasonable and effective.

The paper introduces a new family of privacy attacks on the Web: privacy inferring attack via search engines and presents a privacy inferring model to describe the process and principles of personal privacy inferring attack via search engines. A user‐side automatic detection service is proposed to detect the privacy inference before publishing personal information. In this user‐side service, the authors propose a Privacy Leakage Detection Probability (PLD‐Probability) algorithm. Extensive experiments show these methods are reasonable and effective.