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Management of Innovation and Technology/Management Information Systems.

Information Systems.

SER (Sugar, Energy & Rum) was a company belonging to the Grupo Pellas Corporation. The company operated in four countries, had six subsidiaries, employed more than 25,000 people, had more than 43,500 manzanas of sugarcane crops in Nicaragua alone and had global annual sales of more than US$400m. In 2008, due to the negative effects of the crisis on the company’s business model (increasing costs due to higher prices for fuel and decreasing income because of low international sugar prices), the company decided to implement a business intelligence (BI) system to optimize its processes to reduce costs and increase productivity. At that time, the company had more than 100 years of data, information systems that fed into their main business processes and a culture that appreciated data as the basis for decision-making. However, there were inconsistencies among data systems, users received highly complex reports in Excel or green screens and process monitoring happened long after the tasks had been completed. As a response, SER used extract–transform–load to collect and clean data that would be used in the BI system (the case leaves the questions regarding the systems selection unsolved for discussion). Based on their business model, they selected the most critical processes and defined key performance indicators to measure the impact of changes in those processes. They considered graphic design as a tool to make the system more accepted by users and worked together with users so that reports only offered the most important information. The result was improved costs and productivity. They decreased manual time spent by 14 per cent, automated time spent by 10 per cent, and eliminated 1,556 hours of dead time for equipment in the field, which allowed them to increase productivity by US$1m just in sugar. They saved 20,000 trips from the fields to the factories, which represented more than US$1m in savings by monitoring the weight of wagons loaded with sugarcane in real time. They improved client perceptions about the company both locally and internationally by implementing a sugar traceability system.

The case “Business Intelligence at the Grupo Pellas SER Company” has as its objective to respond to the question: How does a company make its BI system implementation successful? As such, the case: Discusses what a BI system is and what it provides to a business analyses challenges, benefits and context when implementing a BI system; analyses success factors and recommendations in the BI system implementation process; analyses the process of implementing a BI and highlights the importance of the system priority questions and technological alternatives.

Teaching notes are available for educators only. Please contact your library to gain login details or email support@emeraldinsight.com to request teaching notes.

CSS 11: Strategy

Leadership; Political Economy; Strategy; Entrepreneurship.

Masters in Business Administration (MBA); MPhil in Strategic Leadership.

On 5 February 2016, South African entrepreneur Jannie Van Eeden faced a dilemma about whether to expand his current businesses or not. He had to choose between focusing exclusively on hospitality and tourism or dividing his time and resources between the tourism business and expanding his existing logistics business. Expansions to his logistics business would entail investing in a warehouse and supplying fresh produce to the lodges in the wider area of Lake Malawi where he was based. Van Eeden realised that he needed to take into account the political economy of Malawi in unpacking the contextual variables related to his decision. Various stakeholders’ roles are illustrated in the case, for example the government’s role in enabling entrepreneurial businesses as well as the investments made by foreign organisations and international donors.

Development of leaders who can take contextually intelligent decisions. Insights into conducting Political Economy analysis to enable doing business in Africa.

Teaching Notes are available for educators only. Please contact your library to gain login details or email support@emeraldinsight.com to request teaching notes.

CSS 7: Management Science.

Resource-based view (RBV) theory (Barney, 1991; Barney and Mackey, 2016; Nagano, 2020) states that a firm’s tangible and intangible resources can represent a sustainable competitive advantage (SCA), a long-term competitive advantage that is extremely difficult to duplicate by another firm, when it meets four criteria (i.e. not imitable, are rare, valuable and not substitutable). In the context of this case, we believe there are three sources of SCA to be discussed using RBV – the major league soccer (MLS) team player roster, the use of artificial intelligence (AI) technologies to exploit this roster and the league’s single-entity structure: • MLS players: it has been widely acknowledged that a firm’s human resource talent, which includes professional soccer players (Omondi-Ochieng, 2019), can be a source of SCA. For example, from an RBV perspective, a player on the Los Angeles Galaxy roster: > cannot play for any other team in any other league at the same time (not imitable and are rare), > would already be a competitive player, as he is acquired to play in the highest professional league in the country (valuable) and > it would be almost impossible to find a clone player matching his exact talent characteristic (not substitutable) anywhere else. Of course, the roster mix of players must be managed by a capable coach who is able to exploit these resources and win championships (Szymanski et al., 2019). Therefore, it is the strategic human resource or talent management strategies of the professional soccer team roster that will enable a team to have the potential for an SCA (Maqueira et al., 2019). • Technology: technology can also be considered a source of SCA. However, this has been a source of contention. The argument is that technology is accessible to any firm that can afford to purchase it. Logically, any MLS team (or for that matter any professional soccer team) can acquire or build an AI system. For many observers, the only obvious constraint is financial resources. As we discuss in other parts of the case study, there is a fan-based assumption that what transpired in major league baseball (MLB) may repeat in the MLS. The movie Moneyball promoted the use of sabermetrics in baseball when making talent selection (as opposed to relying exclusively on scouts), which has now evolved into the norm of using technology-centered sports analytics across all MLB teams. In short, where is the advantage when every team uses technology for talent management? However, if that is the case, why are the MLB teams continuing to use AI and now the National Basketball Association (NBA), National Football League (NFL) and National Hockey League are following suit? We believe RBV theorists have already provided early insights: > “the exploitation of physical technology in a firm often involves the use of socially complex firm resources. Several firms may all possess the same physical technology, but only one of these firms may possess the social relations, cultural traditions, etc., to fully exploit this technology to implementing strategies…. and obtain a sustained competitive advantage from exploiting their physical technology more completely than other firms” (Barney, 1991, p. 110). • MLS League Single-Entity Structure: In contrast to other professional soccer leagues, the MLS has one distinct in-built edge – its ownership structure as a single entity, that is as one legal organization. All of the MLS teams are owned by the MLS, but with franchise operators. The centralization of operations provides the MLS with formidable economies of scale such as when investing in AI technologies for teams. Additionally, this ownership structure accords it leverage in negotiations for its inputs such as for player contracts. The MLS is the single employer of all its players, fully paying all salaries except those of the three marquees “designated players.” Collectively, this edge offers the MLS unparalleled fluidity and speed as a league when implementing changes, securing stakeholder buy-ins and adjusting for tailwinds. The “socially complex firm resources” is the unique talent composition of the professional soccer team and most critically its single entity structure. While every team can theoretically purchase an AI technology talent management system, its application entails use across 30 teams with a very different, complex and unique set of player talents. The MLS single-entity structure though is the resource that supplies the stability required for this human-machine (technology) symbioses to be fully accepted by stakeholders such as players and implemented with precision and speed across the entire league. So, there exists the potential for each MLS team (and the MLS as a league) to acquire SCA even when using “generic” AI technology, as long as other complex firm factors come into play.

This case relied on information that was widely reported within media, press interviews by MLS officials, announcements by various organizations, journal articles and publicly available information on MLS. All of the names and positions, in this case, are actual persons.

MLS started as a story of dreaming large and of quixotic adventure. Back in 1990, the founders of the MLS “sold” the league in exchange for the biggest prize in world soccer – the rights to host the 1994 Fédération Internationale de Football Association World Cup before they even wrote up the business plan. Today, the MLS is the highest-level professional men’s soccer league competition in the USA. That is a major achievement in just over 25-years, as the US hosts a large professional sports market. However, MLS has been unable to attract higher broadcasting value for its matches and break into the highest tier of international professional soccer. The key reason is that MLS matches are not deemed high quality content by broadcasters. To achieve higher quality matches requires many inputs such as soccer specific stadiums, growing the fan base, attracting key investors, league integrity and strong governance, all of which MLS has successfully achieved since its inception. However, attracting high quality playing talent is a critical input the MLS does not have because the league has repeatedly cautioned that it cannot afford them yet to ensure long-term financial sustainability. In fact, to guarantee this trade-off, the MLS is one of the only professional soccer leagues with an annual salary cap. So, the question is: how does MLS increase the quality of its matches (content) using relatively low cost (low quality) talent and still be able to demand higher broadcast revenues? One strategy is for the MLS to use AI playing technology to extract higher quality playing performance from its existing talent like other sports leagues have demonstrated, such as the NFL and NBA. To implement such a radical technology-centric strategy with its players requires the MLS to navigate associated issues such as human-machine symbioses, risking fan acceptance and even altering brand valuation.

The case is written and designed for a graduate-level (MBA) class or an upper-level undergraduate class in areas such as contemporary issues in management, human resource management, talent management, strategic management, sports management and sports marketing. The case is suitable for courses that discuss strategy, talent management, human resource management and brand strategy.

This case, along with its B case (UVA-QA-0865), is an effective vehicle for introducing students to the use of machine-learning techniques for classification. The specific context is predicting customer retention based on a wide range of customer attributes/features. The specific techniques could include (but are not limited to): regressions (linear and logistic), variable selection (forward/backward and stepwise), regularizations (e.g., LASSO), classification and regression trees (CART), random forests, graduate boosted trees (xgboost), neural networks, and support vector machines (SVM).

The case is suitable for an advanced data analysis (data science, machine learning, and artificial intelligence) class at all levels: upper-level business undergraduate, MBA, EMBA, as well as specialized graduate or undergraduate programs in analytics (e.g., masters of science in business analytics [MSBA] and masters of management analytics [MMA]) and/or in management (e.g., masters of science in management [MScM] and masters in management [MiM, MM]).

The teaching note for the case contains the pedagogy and the analyses, alongside the detailed explanations of the various techniques and their implementations in R (code provided in Exhibits and supplementary files). Python code, as well as the spreadsheet implementation in XLMiner, are available upon request.

Data used to develop the case included primary data from employees and supervisors of a commercial floorcovering manufacturing plant in Northwest Georgia. The case company is not disguised.

The survey was developed using existing instruments from the Organizational Behavior and Human Resources Literature. Instruments were listed in Exhibits 2 through 7. The survey administration had the support of the Vice President for Resources and Facilities, and employees and their supervisors were given time to complete the surveys. The data gathered was analyzed by the researcher using SPSS statistical software.

Established in 1957, J&J started as a family-owned business but had grown and diversified its product offerings by focusing on commercial flooring. It survived several economic downturns and remained competitive in a market dominated by more prominent flooring manufacturers. J&J Industries strived to empower its 800 employees with various incentive programs. Employees remained loyal to J&J; many had worked for the company for over 15 years. However, management wanted to measure the impact of empowering and initiatives on employee performance and satisfaction to determine the real power of employee incentive programs. The Resources and Facilities Vice President employed Professor Lopez, a Management Professor, to develop a survey to measure these constructs and analyze the data to guide future incentive programs. Data from the employee and supervisor survey was provided along with the statistical analysis results for interpretation and recommendations for VP Fordham.

The target audience for this case is primarily students in a research methodology course and students studying quantitative regression analysis and interpretation. The focus is predominantly on graduate-level students in Master of Business Administration or Master of Accounting programs in business. Graduate students should have completed courses in management or organizational behavior, business statistics or quantitative methods or data visualization and cleaning as background knowledge for this case. Specifically, students should understand regression analysis and know when and how the tool is used for managerial decision-making.

Leadership style and organizational change.

The case study level is rated medium to difficult depending on the depth of the analysis undertaken. Managers and executives who undergo training in leadership related issues will benefit from the case study through development of analytical- and decision-making skills. In addition, this case study is written for high level managers and postgraduate students in business courses.

This case study revolves around a man whose name is Rozano Saad. He was a man with strong will, imagination, and ready to explore the new world of Huntsman Tioxide. To him, development of people was necessary. Development of people is the process of getting people to progress from dependent to socially and economically self-reliant. This man with positive views saw difficulties with enthusiasm and noted obstacles as opportunities. He was brave enough to go that extra mile into moulding the organization in the “right pattern.” He was an optimistic angel who was sent to the bleak area of Teluk Kalong, though others might just pack their bags and leave. He was eager for improvement and never stopped looking for ways to make the situation better.

The target users of the case study are expected to:

• Identify the critical success factors (CSFs) of successful leader.

• Examine the leadership and decision making styles employed by the leader.

• Develop the competencies or capabilities of a leader.

• Determine programmes or initiatives and strategies used by the leader in transforming the organization.

• Apply the lesson learnt of a successful leader to their organization.

Identify the critical success factors (CSFs) of successful leader.

Examine the leadership and decision making styles employed by the leader.

Develop the competencies or capabilities of a leader.

Determine programmes or initiatives and strategies used by the leader in transforming the organization.

Apply the lesson learnt of a successful leader to their organization.

Teaching notes.

Public Health; Leadership; Organisational Development; Organisational Behaviour; Public Administration Management.

Postgraduate level for honours or masters programmes in courses on public health; executive leadership and management programmes; MBA level.

The case unpacks decentralisation as a means to promote and improve local decision-making and accountability through community participation and engagements. Ayanda Nkele was a programme manager in a health district in South Africa. He was faced with many challenges when trying to implement his programme, most of which were related to local authority, responsibilities and decision-making abilities at his level. This case describes briefly the South African health system. and how it functions. It describes the proposed changes to the health system and its transformation towards Universal Health Coverage. The decision space analysis as discussed in the case illustrates the types of decentralisation in the country and how this also applies to Nkele’s level.

Understanding the concepts and principles of decentralisation within the context of strengthening district health services, the re-engineering of primary health care (PHC) and rolling out a National Health Insurance in South Africa. Applying the “decision space” approach to analyse the extent of decentralisation. Grasping the requirement of leaders to be “contextually intelligent” and identify the important contextual variables to take into account when analysing public health care.

Teaching Notes are available for educators only. Please contact your library to gain login details or email support@emeraldinsight.com to request teaching notes.

CSS 7: Management Science.

With the development of inclusive financial business in China in recent years, this case describes the credit risk control of “mobile credit”, a smart online credit platform launched by Shanghai Mobanker Co. Ltd. (referred to as “Mobanker”, previously named as “Shanghai Mobanker Financial Information Service Co., Ltd.”) which provides technical services for inclusive finance industry.

Launched in 2014, Amazon's Echo and Echo Dot smart speakers led the category's rapid adoption by households and enabled the penetration of artificial intelligence (AI) voice assistants into the everyday lives of millions of people. By 2019, Alexa the virtual brains behind Amazon's smart speakers was able to play music, create reminders, get weather reports, control lights and other home appliances, shop, and do much more in response to voice commands. Amazon had developed significant new capabilities for Alexa, developed an entire ecosysgtem around it, expanded Alexa's user base to more than 100 million users, and made significant progress in monetizing its digital voice assistant. However, Alexa's progress also created new challenges for Amazon, its Alexa-enabled customers, and society at large. Amazon needed to identify and address these challenges in order to encourage continued consumer acceptance and preclude detrimental government or regulatory action.

Organizational Development; Change Management; Leadership; Healthcare Management Operations; Supply Chain.

MBA; Masters in Healthcare Management; Post-graduate Diploma in Leadership; MPhil in Strategic Leadership.

On April 16, 2016, the CEO of Prince Mshiyeni Memorial hospital, Kwa-Zulu Natal, South Africa, Dr Sandile Tshabalala reflected as he drove through the winding hills of the Cato range. In recent years, the hospital had been a subject of negative publicity with horror stories about patients collapsing while waiting for their medication at one of Durban’s largest hospitals. The case features a number of stakeholders and their demands and even threats. Contextual leadership intelligence requires accurate identification of relevant stakeholders and then involvement in solutions. The case illustrates how these demands had been listened to and how the stakeholders had been involved in finding solutions. A remarkable solution was to realize that the bottleneck at the pharmacy was actually caused by a problem early on in the process, for example, the late start of administrative staff who had to submit patients. A further solution was to utilize the primary health care clinics and even churches for dispensing chronic medicine.

Gaining insight and foresight into the operations and supply chain dilemmas in public health care. Developing understanding of the impact of various stakeholders in the healthcare sector. Understanding buy-in when leading change. Acquiring contextual leadership intelligence in the public health environment.

Teaching Notes are available for educators only. Please contact your library to gain login details or email support@emeraldinsight.com to request teaching notes.

CSS 7: Management Science.