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A reprint of the article "The Secret to AI Is People" by Nada R. Sanders and John D. Wood, which appeared on HBR.org on August 24, 2020, is presented. The importance of a business model where machines and humans are integrated to complement each other is noted. A four-layer framework focusing on intentionality, integration, implementation, and indication is proposed. Several exemplary companies including Apple, Zappos, and Siemens are discussed.

The article discusses the skills that employees need to effectively work with artificial intelligence (AI). The authors conducted interviews with CEOs and found that there is a shift in focus towards developing individual human competencies. The two categories of skills identified as critical are effective interpersonal skills and domain expertise. While technical skills are important, it is the uniquely human skills that are in short supply. The article also provides a framework for implementing AI in organizations, emphasizing the importance of intentionality, integration, implementation, and indication. The authors argue that humans with enhanced skills should be "in the loop" with AI, as AI is copyable, subject to inaccuracies, and requires human critical thinking. [Extracted from the article]

The 4-mm punch biopsy is a minimally invasive standardized approach to diagnosing suspicious periocular eyelid lesions averting unnecessary tissue sacrifice. The authors evaluated a very large cohort of diagnostic periocular punch biopsies.

Since its introduction over three decades ago, the field of supply chain management (SCM) has undergone numerous transformations. Today it is a prevailing theme in scholarly and popular research, and numerous disparate disciplines claim its ownership. Despite the field's evolution there continues to be little agreement on the domain and unifying theory of SCM, as well as a consensus definition. The result has been a lack of clarity as to the scope of SCM, 'siloed' research methodologies, and parallel research efforts. We interviewed 50 academic scholars across disciplines, as well as 20 SCM business executives, to extract commonality of opinion and discuss the future of SCM. The most important of these findings are the identification of common ground' regarding the definition and scope of SCM, establishment of the need for interdisciplinary research, the recognition of the existence of 'inner' and 'outer core' functions central to SCM, and the nature of functional involvement in interdisciplinary research. In this paper we present these findings and provide a path forward based on the collective wisdom of these scholars and executives. Keywords: supply chain management; purchasing/operations; purchasing/IS, INTRODUCTION The field of supply chain management (SCM) has undergone significant development and change over the past three decades, as the term was first coined by Keith Oliver in a [...]

The study of supply chain management must use multiple and complementary methodologies, including econometrics. The field should avoid creating and adopting a dogmatic position excluding valid methodologies to maintain its integrity.

A study was conducted to propose a model that relates the pattern of supplier use of information technology (IT) to specific types of supply chain coordination activities. Ways on how exploitation and exploration relate to operational and strategic coordination. Findings indicate that suppliers must ultimately use IT for both exploitation and exploration.

The growth of outsourcing has resulted in numerous different outsourcing arrangements, ranging from out-tasking and managed services to business process outsourcing and transformational outsourcing. The growing lexicon of outsourcing terminology has caused confusion for many managers and academicians alike, who tend to view outsourcing as a fixed, discrete event or a simple make-or-buy decision. In reality, outsourcing is an umbrella term that includes a range of sourcing options that are external to the firm. Understanding these options, their characteristic differences, and how they serve to meet differing business objectives is the focus of the current research. Based on in-depth interviews with 19 senior executives experienced in outsourcing, as well as a thorough synthesis of available research, this article provides a framework clarifying the broad spectrum of outsourcing arrangements, and their inherent risks and advantages. Managerial guidance related to outsourcing is also provided., INTRODUCTION Outsourcing has become a megatrend in many industries, most particularly in logistics and supply chain management (Feeney, Lacity and Wilcox 2005). The overall scope of outsourcing is continuing to [...]

Deployment of interorganizational information technology (IT) throughout supply chain networks has usually been championed by supply chain network leaders--large firms that typically dominate a supply chain network. In order to participate in a particular network, supplier firms must acquire the requisite IT enabling them to be technologically aligned with the network leader. This is an important decision for supplier firms that are typically smaller in size and must allocate larger portions of their budgets to acquire the necessary IT. This study evaluates the benefits gained by suppliers when investing in interorganizational IT that is aligned with their primary buyer or network leader. The findings show that IT alignment between supplier and buyer has a direct positive impact on both strategic and operational performance measures of the supplier. In addition, IT alignment impacts these performance measures indirectly as it encourages integration between firms., INTRODUCTION Supply chain management (SCM), based on the need for coordination between supply chain partners (Narasimhan and Jayaram 1998; Vakharia 2002; Prahinski and Benton 2004), has been particularly impacted by [...]

Outsourcing has become an increasingly attractive option these days. But for companies operating large distribution networks, particularly on a global scale, making the right outsourcing decision can be a complicated--and [...]

Self‐assessment is increasingly implemented in medical professions’ curricula. In this research, the authors measure the effects of self‐assessment within a preclinical removable prosthodontics course among dental students in a private dental school according to the European qualifications framework descriptors. Thirty subjects, all fourth‐year dental students, were included in this experiment. Fifteen subjects were included in each of the experimental and control groups during one semester. The experimental group subjects used the study roadmap tool in their preclinical tasks. The control group subjects executed the same preclinical tasks under instructor supervision only. All subjects were filmed, and an autonomy score was given to every subject per session. At the end of the semester, cognitive skills development was compared using the Kember et al. questionnaire while practical skills development was compared using a comparison of grades. Two focus groups were undertaken with experimental group subjects. Qualitative and quantitative data were collected and statistically analyzed (p< 0.005). Subjects from the experimental group showed development in critical thinking, practical skills, autonomy, and taking responsibility, thus development in the competence level. Implementation of self‐assessment within preclinical courses may develop skills and competence among dental students, yet more studies are needed.

Results are presented from a study designed to identify competitive strategies of high-growth manufacturers, characteristics that define those strategies, and their success relative to market share. The study is based on a survey of 219 high-growth U.S. manufacturing plants. Four unique competitive strategies are identified: (1) supplier partnership strategy, (2) quality-focused strategy, (3) cost-containment strategy, and (4) time-based competitive strategy. Our findings show that the nature of the manufacturer-supplier relationship can vary greatly depending on the strategy employed; variations include the types of suppliers used and their geographic location. Findings also show that not all strategies are equally effective relative to market share. The supplier partnership and time-based strategies, which emphasize long-term partnering, information sharing, and early supplier involvement, are the most effective. The cost-containment strategy, with its focus on competitive bidding and adversarial negotiations, is found to be least effective although it is prevalent in practice., To reduce costs and improve quality and responsiveness many firms have made manufacturing and supply chain management a cornerstone of their corporate strategy [1, 3]. Historically, corporate strategy objectives were [...]

Parkinson’s disease (PD) is a neurodegenerative disorder with slow progression whose symptoms can be identified at late stages. Early diagnosis and treatment of PD can help to relieve the symptoms and delay progression. However, this is very challenging due to the similarities between the symptoms of PD and other diseases. The current study proposes a generic framework for the diagnosis of PD using handwritten images and (or) speech signals. For the handwriting images, 8 pre-trained convolutional neural networks (CNN) via transfer learning tuned by Aquila Optimizer were trained on the NewHandPD dataset to diagnose PD. For the speech signals, features from the MDVR-KCL dataset are extracted numerically using 16 feature extraction algorithms and fed to 4 different machine learning algorithms tuned by Grid Search algorithm, and graphically using 5 different techniques and fed to the 8 pretrained CNN structures. The authors propose a new technique in extracting the features from the voice dataset based on the segmentation of variable speech-signal-segment-durations, i.e., the use of different durations in the segmentation phase. Using the proposed technique, 5 datasets with 281 numerical features are generated. Results from different experiments are collected and recorded. For the NewHandPD dataset, the best-reported metric is 99.75% using the VGG19 structure. For the MDVR-KCL dataset, the best-reported metrics are 99.94% using the KNN and SVM ML algorithms and the combined numerical features; and 100% using the combined the mel-specgram graphical features and VGG19 structure. These results are better than other state-of-the-art researches.

Accurate forecasting is one of the most critical issues for business planning. Knowing how best to generate forecasts and how others are performing this function is important information for managers. This study reports on forecasting practices in US firms based on a survey of 500 companies. In addition to information on techniques and software used, this survey attempts to gain insights into managerial forecasting practices. These include identifying common causes of forecast errors, typical problem areas, and plans for the future to improve forecasting. Based on these findings specific implications for managers are developed.

Important company decisions covering production planning, workforce scheduling, inventory management, purchasing, capital budgeting, and resource allocations rely on forecasts. A survey was conducted to understand the forecasting practices of manufacturing companies. Results show that forecasters depend heavily on judgmental forecasting methods made in a structured fashion in group settings. Most of the respondents said that they have problems with forecast accuracy. There are plans to implement improvements to overcome such problems.

To make good forecasting decisions, practitioners need to have a clear understanding of how to measure forecast accuracy. This article is a summary of some of the key issues in understanding and using forecast error measures. Practical suggestions for using some of the more popular forecast error measures are provided. Some less common alternatives are also presented.

The advantages of combining judgmental forecasts in operations management with those developed from statistical models are studied. Judgmental forecasts based on knowledge obtained from experience are compared with judgmental forecasts based on knowledge acquired from studying forecasting models and data analysis. Findings indicate that forecasts based on practical experience provide more accuracy.

The implementation of formal statistical forecasting can create a number of problems Introduction Organizational forecasting is the process of estimating future events for the purpose of effective planning and decision [...]

Unlike many disciplines, supply chain management (SCM) is unique in that it is truly a boundary spanning function. At least in theory, it is a discipline that is intertwined with [...]

Health care organizations can optimize the success of their quality programs, and learn about various aspects of changes in organizational culture and processes from the experiences of other similar organizations. Quality implementation experiences of several hospitals reveal the importance of supportive culture, physician participation, adequate program planning and training for successful implementation. Lack of time, support, staff education, difficulty in obtaining data, and employee and physician resistance are some of the problems that impede program implementation.

Our research reveals the continued and evolving role of the human factor in decision making in digitalized retail supply chains. We compare managerial roles in a pre‐ and post‐COVID era through conducting in‐depth interviews of 25 executives spanning the retail supply chain ecosystem. We use grounded theory to develop four main contributions. First, we find that the involvement of managerial judgment is found to be progressively greater moving up the retail supply chain, away from the customer and the demand signal. Second, integration of analytics and judgment is now the primary method of decision making, and we identify elements needed for success. Third, we develop an essential framework for a successful integration process. Fourth, we isolate the necessary components of a successful process for analytics/artificial intelligence (AI) implementation. Our paper offers important insights into how analytics and AI are—and should be used—in judgment and decision making and opportunities for researchers to understand the changing role of the human factor in digitalized retail supply chains.

A study is conducted to develop a methodology to combine both judgmental and traditional forecasting methods, using various integration methodologies.

Sustainability has become a global corporate mandate with implementation impacted by two key trends. The first is recognition that global supply chains have a profound impact on sustainability which requires “greening” the entire supply chain. The second is technology—digitization, artificial intelligence (AI), and “big data”—which have become ubiquitous. These technologies are impacting every aspect of how companies organize and manage their supply chains and have a powerful impact on sustainability. In this essay, we synthesize current dominant themes in research on sustainable supply chains in the age of digitization. We also highlight potential new research opportunities and challenges and showcase the papers in our STF.

Big data analytics has become an imperative for business leaders across every industry sector. Analytics applications that can deliver a competitive advantage appear all along the supply chain decision spectrum—from targeted location-based marketing to optimizing supply chain inventories to enabling supplier risk assessment. While many companies have used it to extract new insights and create new forms of value, other companies have yet to leverage big data to transform their supply chain operations. This article examines how leading companies use big data analytics to drive their supply chains and offers a framework for implementation based on lessons learned.

We develop a novel online real-time scheduling algorithm with applications for healthcare diagnostic centers to deal with walk-in patients based on a set of constraints on the sequence of tests and resources. The problem is especially significant at healthcare centers in developing and emerging nations, such as India, where appointment schedules do not work. Within this realistic context, our objective is to improve patient satisfaction by reducing waiting time and improve diagnostic center performance through better utilization of the constrained resources. We propose a Mixed Integer Linear Programming (MILP) formulation to represent diagnostic centers as a Flow and Open Shop, to capture the system dynamics of the Flexible Hybrid Shop Scheduling Problem. We then develop a novel Online Genetic Algorithm (OGA) capable of solving real life large scale problems, as Open Shop scheduling problems are NP-hard. The developed OGA is first validated for small instances against a theoretical lower bound and the MILP model using CPLEX solver for flow time and makespan. The OGA is then empirically validated with data collected from two diagnostic centers of different sizes and configurations. For both centers, the developed OGA shows significant improvement compared to the simulation model. This research offers an important contribution to both literature and practice as it is one of the first to model the patient scheduling problem as an online real-time process. Implementing the developed OGA would help diagnostic centers significantly improve time estimates, thus reducing actual patient time and improving the efficiency of the system. Most importantly, the OGA is generalizable beyond healthcare to a broad range of environments that share Hybrid Shop characteristics.

Research on benchmarking has been extensive. It has not addressed the issue of how benchmarking impacts the capabilities or performance of firms. Benchmarking efforts may lead to either failure preventing or success producing capabilities. As firm capabilities evolve over time, it is critical to understand when benchmarking discoveries and eventual process changes, become success producers. A failure preventer may result from a firm using benchmarking practises to ‘stay in the game’ or status quo, merely maintaining their existence and resulting in efficiency as opposed to effectiveness. In this study, we relate research on operational strategy, capabilities, and firm performance to extend Varadarajan’s research in the context of benchmarking in order to specifically identify when benchmarking is a success producer, leading to capabilities that result in a sustainable, competitive advantage. We develop a conceptual framework to demonstrate these linkages.

Every executive has heard about the importance of Lean as a means of eliminating waste and “fat.” However, when operations are novel and complex–as in product development, research, information technology, and many other kinds of projects–cutting out the “fat” turns out to be much more challenging. To understand Lean in an environment characterized by extreme novelty and complexity, we drew on our experiences with a number of processes, and in particular Lockheed Martin's Lean implementation for the F-22 fighter aircraft. Our findings lead to a path that executives and managers can follow to become Lean without compromising innovation.

Identification of pathological events in the renal allograft using protocol biopsies at predetermined time intervals may yield useful information and improve outcomes. We examined the influence of decisions taken on the basis of 1‐ and 3‐month protocol biopsies findings on 1‐year renal allograft function in a prospective randomized study. Out of 102 living‐donor allograft recipients, 52 were randomized to undergo protocol biopsies and 50 controls had only indicated biopsies. All acute rejection (AR) episodes (clinical and subclinical) were treated. Calcineurin inhibitor (CNI) dose adjustments were made on clinical judgment. Baseline recipient and donor characteristics, immunosuppressive drug usage, HLA matches and 2‐h cyclosporine levels were similar in both groups. At 1 and 3 months, protocol biopsies revealed borderline (BL) changes in 11.5% and 14% patients, AR in 17.3% and 12% and chronic allograft nephropathy (CAN) in 3.8% and 10%. The incidence of clinically evident AR episodes was similar in the two groups, but biopsy group had lower serum creatinine at 6 months (p = 0.0003) and 1 year (p < 0.0001). The renal functions were similar in those with normal histology and BL changes. Protocol biopsies are helpful in detecting subclinical histological changes in the graft and improving short‐term renal allograft function.

Marked effect of imposed low frequency oscillations with amplitudes of 6.6 × 10−4−11.6 × 10−4during creep of pre-aged Al-40 wt.% Zn alloy samples under constant stress at 423 K, was observed. Increasing the frequency or amplitude at a certain temperature, increased both nand ${\dot \varepsilon}_{\rm st}$but decreased βvalues. The value of the ratio γ(0.75−0.77) shows the high dependence of the steady creep on the transient creep stage. The results were explained in view of the nature of the thermally induced structures during aging and their mode of interaction with lattice defects generated by the applied stress and the imposed oscillations. Grain boundary sliding and grain boundary diffusion of Zn and Al are suggested as the rate controlling mechanisms for both the transient and steady creep stages, respectively.

Typical compositions of austempered ductile cast irons in different metallurgical states were studied with the aim of making a detailed assignment of thermal effects seen using differential scanning calorimetry (DSC) to transformations occurring in the alloy phase constitution and microstructure. In austempered specimens the transformation of retained austenite is revealed by an exothermic reaction at temperatures above 450°C which depend on the content of alloying elements. Martensite transformations are seen in a wide temperature range starting at ~100°C and giving exothermic and endothermic overlapped DSC signals due to relaxation, carbon diffusion, and tempering. It is concluded that DSC is a powerful tool for detecting tiny traces of martensite in austempered materials.

Differentiation of marine luminous bacteria using Biolog GN plate combined with API 20e or the BBL Crystal ID plate inoculated with cell suspensions in artifical seawater was accomplished by comparison to type species using cluster analysis. Inoculum density affected the results from Biolog GN plates, but had less of an effect on the reactions obtained from API 20e strip or BBL Crystal ID plate. In a few cases, combination of the Biolog GN traits along with either the API 20e or Crystal ID traits was necessary to differentiate some marine luminous bacteria. © 1998 John Wiley & Sons, Ltd.

This paper presents a new theoretical technique for the study of defects in crystals. The methods is based on an ab-initio Hartree-Fock perturbed-cluster (PC) scheme1. A prerequisite for this technique is the availability of a model for the host, perfect crystal, that must be obtained with the same Hamiltonian and the same computational conditions (basis set, accuracy etc.). This information is provided by CRYSTAL, an ab-initio periodic Hartree-Fock code2.

a-quartz and stishovite have been studied using a periodic ab-initio Hartree-Fock method in order to characterize the chemical nature of the Si-O bond and the way in which it changes with the coordination number of Si. Structural properties, including unit cell volume and c/a ratio have been optimized in order to evaluate the reliability of the method and the effect of the basis set. Density of states and electron charge density maps have been taken into account to investigate the electronic properties of the two systems and the rôle played by different orbitals. We also present comparisons with experimental X-ray emission data. The importance of d orbitals is stressed by our calculations, and a possible interpretation of the Si-O bond proposed. Quartz is found to be more covalent than stishovite.

We present the results of a theoretical study in which we investigated the properties of topological defects on the (001) MgO surface. We employed a recently developed method that provides an accurate description of local properties near a defect while taking into account the interactions between the defect and the surrounding crystal. We report calculated formation energies for steps and islands of various sizes on this surface and compare those energies to the formation of similar islands in vacuum. In addition, we evaluated the energetic contribution of various low-coordination sites to the total crystal energy. By combining these data and extrapolating the results, we were able to determine the average size of the islands. These results, in conjunction with calculations that evaluated the electronic properties of different defect sites, allowed us to conclude that there is little interaction between low-coordinated sites in a block of adatoms and the ions that comprise the “surface” below. The electrostatic potential acting on low-coordinated sites in a given island is mainly generated by the other co-planar ions in the island.

The article presents a case study of a warehouse environment and the effect of forecast errors on the organizational cost. It states that the organizational cost consequences of forecast errors were evaluated by simulating a labor-intensive warehouse environment. It discusses the significance of accurate forecasting for service organizations. The case study shows that the forecast bias is more likely to impact the organizational cost than forecast standard deviation.

One of the commonest nanoparticles with unique properties is porous silicon nanoparticles (PSNPs). This study aims to prepare PSNPs via an improved method, followed by the investigation of the antimicrobial activity of the synthesized PSPNs against Escherichia coli and Staphylococcus aureus. The synthesis of the PSNPs was executed via a modified electrochemical etching process. After the synthesis, the obtained liquid PSNPs were subjected to laser treatment under an Nd-YAG laser condition of laser energy 350 mJ, and wavelength 1064 nm. The synthesized PSNPs were further characterized for functional groups and surface morphology using Fourier transfer infrared (FTIR) and Scanning Electron Microscopy (SEM), respectively. With E. coli and S. aureusas the commonest implicated organisms in both adult and childreninfections,there is a need to explore novel antimicrobial agents rather than antibiotics for curtailing these bacterial species. The synthesized PSNPs showed potential antibacterial activity against the studied organisms, although the observed antibacterial activities after the combination of PSNPs with Amoxicillin and Cephalexin were higher compared to the activity of PSNPs alone. These complexes were observed to act on the bacterial cytoplasmic membrane and nucleic acid which resulted in an improved cellular permeability due to the loss of membrane integrity and nucleic acid damage. However, there is a need to further investigate the antibacterial activity of PSNPs and its complexes with other antibacterial agents against other disease-causing by other bacterial species.