There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

Machine Learning is the study of methods for programming computers to learn. Computers are applied to a wide range of tasks, and for most of these it is relatively easy for programmers to design and implement the necessary software. However, there are many tasks for which this is difficult or impossible. These can be divided into four general categories. First, there are problems for which there exist no human experts. For example, in modern automated manufacturing facilities, there is a need to predict machine failures before they occur by analyzing sensor readings. Because the machines are new, there are no human experts who can be interviewed by a programmer to provide the knowledge necessary to build a computer system. A machine learning system can study recorded data and subsequent machine failures and learn prediction rules. Second, there are problems where human experts exist, but where they are unable to explain their expertise. This is the case in many perceptual tasks, such as speech recognition, hand-writing recognition, and natural language understanding. Virtually all humans exhibit expert-level abilities on these tasks, but none of them can describe the detailed steps that they follow as they perform them. Fortunately, humans can provide machines with examples of the inputs and correct outputs for these tasks, so machine learning algorithms can learn to map the inputs to the outputs. Third, there are problems where phenomena are changing rapidly. In finance, for example, people would like to predict the future behavior of the stock market, of consumer purchases, or of exchange rates. These behaviors change frequently, so that even if a programmer could construct a good predictive computer program, it would need to be rewritten frequently. A learning program can relieve the programmer of this burden by constantly modifying and tuning a set of learned prediction rules. Fourth, there are applications that need to be customized for each computer user separately. Consider, for example, a program to filter unwanted electronic mail messages. Different users will need different filters. It is unreasonable to expect each user to program his or her own rules, and it is infeasible to provide every user with a software engineer to keep the rules up-to-date. A machine learning system can learn which mail messages the user rejects and maintain the filtering rules automatically. Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis. Statistics focuses on understanding the phenomena that have generated the data, often with the goal of testing different hypotheses about those phenomena. Data mining seeks to find patterns in the data that are understandable by people. Psychological studies of human learning aspire to understand the mechanisms underlying the various learning behaviors exhibited by people (concept learning, skill acquisition, strategy change, etc.).

Machine learning

MKT 6009 Marketing Internship (0 semester credit hours) Student gains experience and improves skills through appropriate developmental work assignments in a real business environment. Student must identify and submit specific business learning objectives at the beginning of the semester. The student must demonstrate exposure to the managerial perspective via involvement or observation. At semester end, student prepares an oral or poster presentation, or a written paper reflecting on the work experience. Student performance is evaluated by the work supervisor. Pass/Fail only. Prerequisites: (MAS 6102 or MBA major) and department consent required. (0-0) S MKT 6244 Digital Marketing Strategy (2 semester credit hours) Executive Education Course. The course explores three distinct areas within marketing and sales namely, digital marketing, traditional sales prospecting, and executive sales organization and strategy. The continuing convergence of the digital marketing and sales funnels has created a strategic continuum from digital lead generation to digital sales. The course identifies the current composition of this digital continuum while providing opportunities to evaluate sales and marketing digital strategies. Prerequisites: MKT 6301 and instructor consent required. (2-0) Y MKT 6301 (SYSM 6318) Marketing Management (3 semester credit hours) Overview of marketing management methods, principles and concepts including product, pricing, promotion and distribution decisions as well as segmentation, targeting and positioning. (3-0) S MKT 6309 Marketing Data Analysis and Research (3 semester credit hours) Methods employed in market research and data analysis to understand consumer behavior, customer journeys, and markets so as to enable better decision-making. Topics include understanding different sources of data, survey design, experiments, and sampling plans. The course will cover the techniques used for market sizing estimation and forecasting. In addition, the course will cover the foundational concepts and techniques used in data visualization and \"story-telling\" for clients and management. Corequisites: MKT 6301 and OPRE 6301. (3-0) Y MKT 6310 Consumer Behavior (3 semester credit hours) An exposition of the theoretical perspectives of consumer behavior along with practical marketing implication. Study of psychological, sociological and behavioral findings and frameworks with reference to consumer decision-making. Topics will include the consumer decision-making model, individual determinants of consumer behavior and environmental influences on consumer behavior and their impact on marketing. Prerequisite: MKT 6301. (3-0) Y MKT 6321 Interactive and Digital Marketing (3 semester credit hours) Introduction to the theory and practice of interactive and digital marketing. Topics covered include: online-market research, consumer behavior, conversion metrics, and segmentation considerations; ecommerce, search and display advertising, audiences, search engine marketing, email, mobile, video, social networks, and the Internet of Things. (3-0) T MKT 6322 Internet Business Models (3 semester credit hours) Topics to be covered are: consumer behavior on the Internet, advertising on the Internet, competitive strategies, market research using the Internet, brand management, managing distribution and supply chains, pricing strategies, electronic payment systems, and developing virtual organizations. Further, students learn auction theory, web content design, and clickstream analysis. Prerequisite: MKT 6301. (3-0) Y MKT 6323 Database Marketing (3 semester credit hours) Techniques to analyze, interpret, and utilize marketing databases of customers to identify a firm's best customers, understanding their needs, and targeting communications and promotions to retain such customers. Topics

Marketing for management.

行銷硏究 : Marketing research

This handbook looks to provide academics and students with a comprehensive and holistic understanding of the phenomenon of innovation. Innovation spans a number of fields within the social sciences and humanities: Management, Economics, Geography, Sociology, Politics, Psychology, and History. Consequently, the rapidly increasing body of literature on innovation is characterized by a multitude of perspectives based on, or cutting across, existing disciplines and specializations. Scholars of innovation can come from such diverse starting points that much of this literature can be missed, and so constructive dialogues missed. The editors of The Oxford Handbook of Innovation have carefully selected and designed twenty-one contributions from leading academic experts within their particular field, each focusing on a specific aspect of innovation. These have been organized into four main sections, the first of which looks at the creation of innovations, with particular focus on firms and networks. Section Two provides an account of the wider systematic setting influencing innovation and the role of institutions and organizations in this context. Section Three explores some of the diversity in the working of innovation over time and across different sectors of the economy, and Section Four focuses on the consequences of innovation with respect to economic growth, international competitiveness, and employment. An introductory overview, concluding remarks, and guide to further reading for each chapter, make this handbook a key introduction and vital reference work for researchers, academics, and advanced students of innovation. Contributors to this volume - Jan Fagerberg, University of Oslo William Lazonick, INSEAD Walter W. Powell, Stanford University Keith Pavitt, SPRU Alice Lam, Brunel University Keith Smith, INTECH Charles Edquist, Linkoping David Mowery, University of California, Berkeley Mary O'Sullivan, INSEAD Ove Granstrand, Chalmers Bjorn Asheim, University of Lund Rajneesh Narula, Copenhagen Business School Antonello Zanfei, Urbino Kristine Bruland, University of Oslo Franco Malerba, University of Bocconi Nick Von Tunzelmann, SPRU Ian Miles, University of Manchester Bronwyn Hall, University of California, Berkeley Bart Verspagen , ECIS Francisco Louca, ISEG Manuel M. Godinho, ISEG Richard R. Nelson, Mario Pianta, Urbino Bengt-Ake Lundvall, Aalborg

The Oxford Handbook of Innovation

\nPurpose\nAssurance of Halal integrity up to the consumption point requires a supply chain approach. Credence quality attributes of Halal products make adoption and management of Halal practices along the whole supply chain a challenging task. This paper aims to explore and evaluate the barriers in the management of the Halal supply chain.\n\n\nDesign/methodology/approach\nThis paper reviews the contemporary literature regarding Halal and management of Halal supply chain and subsequently identifies significant barriers towards managing the Halal supply chain. Further, these barriers are examined quantitatively using Best Worst Method.\n\n\nFindings\nThis study has established significant barriers to Halal supply chain management. Moreover, prioritisation of barriers gives a hierarchy to mitigate these significant barriers. The analysis suggests that reduced demand for Halal products is the highly weighted barrier. Improper laws to regulate the Halal industry and lack of policy framework are hindering the effective management of the Halal supply chain.\n\n\nResearch limitations/implications\nThis study explored a limited number of barriers; it may be possible that some barriers might not have captured. Further, the identified barriers are generic and validated in the context of multicultural societies. Expert opinion has been used to obtain the weight of barriers which may be biased.\n\n\nOriginality/value\nTo the best of author’s knowledge, no study has categorically explored and presented a holistic framework to mitigate barriers of managing Halal practices in the supply chain.\n

Analysing barriers towards management of Halal supply chain: a BWM approach

Halal supply chain management (HSCM) is an emerging business and research area; there is a need to motivate researchers towards exploring the links between HSCM and sustainable performance of the organisation. Therefore, the purpose of this study is to develop a conceptual framework in order to link the HSCM with sustainable performance.,This review based paper identifies eleven critical factors for effective management of the Halal supply chain (HSC) and provides a conceptual framework for an HSCM after due consultative inputs from experts. The exploratory paper tries to integrate success measures of HSCM through integrity, process quality and customer satisfaction to sustainable performance measures.,Halal label is considered just like a kosher label or a green label or an organic label, which provides confidence to consumers on the Halal aspect of products and services. Some part of the society thinks that Halal products carry a higher value; therefore, the industry wants to identify if HSCM is sustainable. The same is measured comprehensively through environmental performance, social performance and economic performance. Animal welfare, fair trade and perceived benefits, better quality, wholesome with ethical practices help in sustainable development.,This paper tries to contribute to the research of HSCM with sustainable performance measures being embedded in the system. The model, along with researchers, may also help managers of firms dealing with Halal products in understanding how much sustainable their organisation is. This research is from a non-Islamic, democratic country which is multicultural and has large numbers of Halal consumers.

Conceptualising a framework linking halal supply chain management with sustainability: an India centric study

Purpose




Multiplicity and conflicting Halal standards involve unnecessary repetition of testing for demonstrating the Halal integrity of the process and the product, thus making it difficult for the Halal commodities to get traction in international markets. The purpose of this paper is to suggest initiatives to facilitate harmonisation of Halal standards as to eliminate trade barrier of Halal and to assure the availability of Halal consumables to larger masses.




Design/methodology/approach




Ranking of the initiatives for the harmonisation of Halal standards taking in consideration the costs of accomplishment and associated benefits obtained has been done through the application of integrated Interpretive Ranking Process (IRP) and Fuzzy Total Interpretive Structural Modelling (Fuzzy TISM). This integrated methodology with the weighted criteria have refined the value of the net dominance of different variables, thereby increasing the efficacy of IRP in decision making.




Findings




Findings suggest that strengthening the strategic coordination and collaboration among competent HCBs is a significant initiative. This initiative needs to be undertaken to mitigate the conflict between HCBs. This necessitates to develop a common platform in making the collective decision for effectively controlling Halal businesses. Moreover, recognising competent HCBs will prompt the effective implementation and execution of Halal standards across the supply chain, and ease the global trading of Halal products. A framework has been conceptualised to enable harmonisation of Halal standards which intimates to develop globally agreed protocols for Halal practices.




Practical implications




The framework presented may act as a prelude to harmonise Halal standards and may positively affect the international trade of Halal commodities by phasing out the discriminatory and market-impeding standards.




Originality/value




A harmonised system may provide correct information to the stakeholders and may help in making an informed decision.

Using integrated weighted IRP-Fuzzy TISM approach towards evaluation of initiatives to harmonise Halal standards

The increased population, scarcity of resources and environmental consciousness put the tremendous stress on the organisations to fulfil the demand in sustainable way. The current linear model is based on the take-make-use-destroy model, which has many limitations in terms of resource utilisation and environmental impact. To overcome such limitation, circular economy is proposed. The main aim of circular economy is to create a circular system that maximises the resource value and enhances the material and product. However, the adoption of the circular economy is challenging and required some essential/motivational factor. This study is identifying the ten major drivers towards the adoption of circular economy. Further, these drivers are categorised into two groups utilising the decision-making trial and evaluation laboratory (DEMATEL). The result of this study explored that most influential drivers are ‘government policies for cleaner production’ and ‘urbanisation’, while ‘enhanced material and energy efficiency’ and ‘improving product quality’ are the most influenced. This study can support the policy makers to develop the strategies in the adoption of circular economy.

Investigation of Drivers Towards Adoption of Circular Economy: A DEMATEL Approach

Artificial intelligence (AI) is globally acknowledged as innovative technology. Today, many corporations and individuals are making an effort to harness the capabilities of AI in almost all sectors viz. healthcare, education, manufacturing, smart cities, agriculture, etc. The concept of ‘Smart Factories’ and ‘Industry 4.0’ has prompted many global enterprises to use automation and intelligent robots to improve manufacturing and enhance the quality of the finished product and overall productivity. Indeed, artificial intelligence is a vital tool to augment manufacturing by facilitating the R&D, enhancing the quality, reducing the errors, and maintaining the supply chain by projecting demand forecasting and simulation of outcomes to foster higher margins in stiff competition. However, the requirement is to build an industry that should be compliant with such disruptive changes and a workforce compatible enough to create a collaborative environment for both men and technology to work productively. Thus to conduct this study, several keywords and their combinations were used and explored using Google Scholar. The relevant articles, papers, and journals obtained were examined, and data pertinent to the study were collected, examined, and aggregated. Furthermore, specific changes in the current policies and the working parameter were also suggested. In this paper, the scope of artificial intelligence and its applications in today’s manufacturing sector of India is discussed. Here, the Indian manufacturing sector’s present status is focused primarily, the limitations are identified and how they can be dealt with.

Abid Haleem

Papers

Analysing barriers towards management of Halal supply chain: a BWM approach

Conceptualising a framework linking halal supply chain management with sustainability: an India centric study

Using integrated weighted IRP-Fuzzy TISM approach towards evaluation of initiatives to harmonise Halal standards

Investigation of Drivers Towards Adoption of Circular Economy: A DEMATEL Approach

Artificial Intelligence (AI) and Its Applications in Indian Manufacturing: A Review