NHCE MBA Compendium of R&D Projects

Potential contribution The increasing urbanization with climate change, global warming issues and the related need to decarbonize the economy, is forcing urgency for identifying the alternate source for the global adoption and sustainable scalable solutions. The country’s demographic and road patterns and its natural resources availability provide enormous scope for the electric bike industry. It is a frugal innovation strategy which provide safe carbon free environment, and moreover a part of health rehabilitation programmes. It is required that societal, economic and political and infrastructure systems integrate together to balance the energy environment. With this potential, the era of electric bike started its new avenues on the roads of India specifically focusing on Indian women. To develop this viewpoint, the present study focuses on the preference of e-bike among the commuters in Bangalore region. Conclusion: Electric vehicles are the new buzz word when it comes to the world of automotive. With fossil fuel reserves running out and pollution levels increasing to dangerous levels, an alternative to internal combustion engines is the need of the hour. Electric vehicles run clean and produce zero emissions, making them a popular alternative. systems The top brands that produce electric bikes & scooters in India are Bajaj, Revolt, Hero Electric, Ather, Okinawa. Increased e-bike use can potentially support a shift towards more sustainable and active transport. References: 196

1 K. Schleinitz , T. Petzoldt , L. FrankeBartholdt , J. Krems , T. Gehlert, The German Naturalistic Cycling Study – Comparing cycling speed of riders of different e-bikes and conventional bicycles, ScienceDirectEkseveir July- 2015. 2. Ajinkya Parab, Ankit Kamath, SatwantSingh Rajpurohit, Zeeshan Mulla , Urban Electric Bike , IJSRD - International Journal for Scientific Research & Development| Vol. 3, Issue 02, 2015 ISSN (online): 2321-0613 3. R.S Jadoun , Sushil Kumar Choudhary , Design And Fabrication Of Dual Chargeable Bicycle,InnovativeSystems Design and Engineering, www.iiste.org ISSN2222-1727 (Paper) ISSN 2222-2871 (Online) Vol.5, No.8, 2014. 4.Chetan Mahadik , Sumit Mahindrakar , Prof. Jayshree Deka , An Improved & Efficient Electric Bicycle System With The Power Of Real-time Information Sharing, Multidisciplinary Journal of Research in Engineering and Technology, www.mjret.in ,ISSN:2348-6953 , M15-1-2-7-2014 5. Rahul Sindhwani , Punj L. Singh , Anjum Badar , Ankur Rathi , Design Of Electric Bike With Higher Efficiency , International Journal of Advance Research and Innovation Volume 2, Issue 1 (2014) 247-251 ISSN 2347 - 3258 6. Rajendra Beedu, Ankit, Mohmed Asif Shaik, Sushant Jain, Design, Fabrication And Performance Analysis Of Solar Power Bicycle, International Journal of Renewable Energy and Environmental Engineering ISSN 2348-0157, Vol. 02, No. 03, July, 2014 Title of the paper: HR ANALYTICS- TRANSFORMING TRADITIONAL HR TO NEW AGE PROCESS IN TODAY’S DIGITALIZED ERA NAME OF AUTHOR 1: Dr.Priyameet Kaur Keer NAME OF AUTHOR 2 Dr.Sheelan Misra HR ANALYTICS- TRANSFORMING TRADITIONAL HR TO NEW AGE PROCESS IN TODAY’S DIGITALIZED ERA ABSTRACT: It goes with saying that people are vital to the success of any company. There’s no doubt that any business which can attract the right competencies, manage talent effectively, utilize capacity efficiently, and retain employees is setting itself up for long-term success. HR departments are generating more data than ever before but at the same time they often struggle to turn their data into valuable insights. 197

Developments in Human Resources Management are fast being integrated with corresponding changes in data and information processing, which are restructuring our environments. Focus on HR analytics has increased steadily over the past decade as evidenced by the continuously growing demand of HR analytics in the management decision making process. HR analytics supports data interpretation to recognize trends and take corrective measures for profitable functioning of business. Organizations strive for more innovative business practices to improve efficiency and HR analytics has the highest impact on organizational success. The increasing globalization of the job market combined with an ever increasing shortage of skilful staffs and advances in technology have resulted in large scale changes to the recruitment practices through the use of HR Analytics. This paper highlights how the business analytics provides a multi dimensional approach towards building effective HR strategies for the betterment of the organization, for study secondary source of data is used. Keywords: Competencies, data interpretation, innovative business practice, integrated, retain. INTRODUCTION: In a competitive market scenario, it is imperative that an employee’s potentials be harnessed to the best for organisational success. In such an environment, human resources remain one of the primary distinguishing factors for an organisation that can be used for competitive growth in order to create necessary organisational value. Human resource analytics (HR analytics) is an area in the field of analytics that refers to applying analytic processes to the human resource department of an organization in the hope of improving employee performance and therefore getting a better return on investment. HR has core functions that can be enhanced by applying processes in analytics. These are acquisition, optimization, paying and developing the workforce of the organization. HR analytics can help to dig into problems and issues surrounding these requirements, and using analytical workflow, guide the managers to answer questions and gain insights from information at hand, then make relevant decisions and take appropriate actions. HR analytics is playing major role in today's business changing environment with increased business requirements towards organizational efficiency. It enables better decision making about workforce using employee data. HR analytics supports organizations for mapping HR metrics with strategic business goals. It majorly focuses on acquiring talent to assessing future HR needs by improving employee morale and satisfaction. HR analytics, also called talent or people analytics, is the application of considerable data mining and business analytics techniques to talent data. Analytics that measure performance and efficiencies that matter to HR only. 198

HR analytics is also immensely beneficial in training employees, which is a big part of HR departments. Instead of simply depending on hunch, HR analytics helps in ascertaining the exact training needs for employees, which eventually adds value to individuals and benefits the organisation.Human resource analytics is a relatively novel intervention in the larger domain of HRM, and it refers to the use of statistical tools, measures and procedures, which can be used in employing and masking the most effectual decisions such as HRM strategies and practices. HR analytics is reaching more organizations and extends to a wider range of users, from executives and line of business managers to analysts and other knowledge workers, within Organizations. THE EVOLUTION OF HR ANALYTICS The evolution of HR analytics has come a long way since it was introduced and organizations today have the ability to track all kinds of metrics to ensure that their people analytics, talent analytics, and workforce analytics are accurate .For the past three decades HR professionals and senior executives tirelessly trying to improve the state of HR measurement and to help both understand its importance. These efforts started out at the nuts and bolts level creating definitions for basic HR metrics such as compensation, staffing, hiring and retention. This work laid the foundation for gathering comparable data across organizations, which in turn, enabled the benchmarking of HR metrics. Over the years, a number of scholars and practitioners expanded the benchmarking of HR metrics to include investments in training and developing employees, as well as in a broad array of other HR policies and practices. Refining and improving the benchmarking of HR metrics remained a primary area of focus throughout much of the decades. This benchmarking focus, while helpful in informing HR professionals about how their organization’s HR metrics stacked up to comparable or best-in- class organizations, provided little by way of actionable business intelligence on how to gain competitive advantage through people. This requires a solid grasp of HR analytics: the systematic collection, analysis, and interpretation of data designed to improve decisions about talent and the organization as a whole. The use of analytics is changing the way HR 199

professionals quantify the value that people our biggest asset have on the organization's ability to succeed in the market or in its mission. RESEARCH AIMS AND OBJECTIVES 1. To investigate and gain insight into the future of HR analytics if integrated into the company to assist managers in predictive decision-making based on statistical evidences and relevant HR analytical data and literature. 2. To examine the existing literature on the integration of HR analytics within organisations and evaluate the existing studies qualitatively and discuss the research gaps (if any). 3. To examine the IT infrastructure and technological interventions, including those that affect the way data is mined stored and made in terms of the effective implementation of HR analytics and the need for them in order to be efficient in terms of data storing in order to be relevant for HR analytics. LITERATURE REVIEW 1.S. No Author Title Key Focus & Findings 1 Marten et.al (2013) A Framework for Business Analytics in Performance Management .The paper suggests that with the adequate use of data and analytical methods business dynamics can be controlled. These are called Performance Analytics. 2 Dulebohn &Johnson (2013) Human Resource Metrics and Decision Support: A Classification Framework. This study highlights, the issue is that although HR managers have developed a greater number of metrics, a lack of guidance is still lurking around with respect to where to apply those metrics, and to incorporate them into Distributed Support Systems(DSS) and Business Intelligence tools, eventually adding value to the HR. Hence, a framework is provided along with some guidance to researchers and managers 200

3 Hota & Ghosh (2013) Workforce Analytics Approach: An Emerging trend of Workforce Management In this paper, the author explains the workforce analytics as the new corporate mindset. 4 Kapoor & Sherif (2012) Human Resources in an Enriched Environment of Business Intelligence .The paper signifies one of the most vital problems of educating multinational companies to align their HR processes and practices to the altering global labor market conditions. By adding BI and Data analytics in the DNA of HRM protocols and database strategies they can very well attract develop and retain their top talent and be a fore runner in the global business competition. IMPORTANCE OF HR ANALYTICS IN ORGANIZATION People are organizations unsurpassed assets, and effective way of gaining competitive advantage in a present volatile market environment and it is a big challenge for organizations to manage employees with diversified competencies and mapping their outputs in line with the organizational strategy. This requires creating, analysing and storing vast amount of data to support decision making. A recent global survey on Oracle suggests that HR is right up there with the most analytical functions in business and even a bit ahead of a quantitatively-oriented function like Finance Few HR organizations even had a dedicated analytics person. SAP, IBM, Oracle, Microsoft are vendors in Business Intelligence. BI software’s have HR modules with BI and data analytics capabilities. R-Studio is a data analysis and visualization software tool which can be applied for very large data sets, Python is a preferred programming language of all data scientists for statistical data analysis and visualization. Microsoft Excel is a traditionally a great data analysis tool to collect, analyse and transform data using formulas, pivot tables, scenario building and graph tools. Microsoft Power Business Intelligence software has power to extract data from various sources and makes easy for us to analyse, aggregate and visualization of data. The five major steps of Analytical model include: 1. Track: Extracting, transforming, loading, and integrating data into a data warehouse as well as monitoring data in a real-time or near real-time environment. 201

2. Analyze:. Analysis of data using business intelligence tools such as query, multidimensional analysis and data mining. 3. Model: Formulating a model for forecasting, optimization, and scenario planning by utilize advanced analytics tools. Descriptive and predictive statistical methods are used to scores and other models used in decision making. 4. Decide: Arriving at a decision based on analysis and pre-existing or newly developed models that combine individual and group input facilitated by collaboration tools or personal interaction. 5. Act: Acting to decision based on the particular business process being addressed. Examples include launching a new marketing campaign based on the analysis of previous campaign results, customer behaviour, new promotional plan and inventory levels. HOW HR ANALYTICS CAN BE EFFECTIVE BASED HR TOOL Human resources (HR) or human capital analytics is primarily a communications device. It brings together data from disparate sources, such as surveys, records, and operations, to paint a cohesive, actionable picture of current conditions and likely futures. Analytics is divided into three levels: 1. Descriptive. Traditional HR metrics are largely efficiency metrics (turnover rate, time to fill, cost of hire, number hired and trained, etc.). The primary focus here is on cost reduction and process improvement. Descriptive HR analytics reveal and describe relationships and current and historical data patterns. This is the foundation of your analytics effort. It includes, for example, dashboards and scorecards; workforce segmentation; data mining for basic patterns; and periodic reports. 2. Predictive. Predictive analysis covers a variety of techniques (statistics, modelling, data mining) that use current and historical facts to make predictions about the future. It’s about probabilities and potential impact. It involves, for example, models used for increasing the probability of selecting the right people to hire, train, and promote. 3. Prescriptive. Prescriptive analytics goes beyond predictions and outlines decision options and workforce optimization. It is used to analyze complex data to predict outcomes, provide decision options, and show alternative business impacts. It involves, for example, models used for understanding how alternative learning investments impact the bottom line (rare in HR). Different HR Analytics Tools used by companies: HR analytical tools are those that examine workplace and performance data .The data being uncovered is helping companies to predict employee behaviours, talent gaps and potential turnover, and forecast areas of inefficiency. Some of the tools are listed below: 1. R Studio 2. Python 3. Excel 4. SPSS 202

5. Predictive analysis 6. Visual HR metrics HR analytics is also immensely beneficial in training employees, which is a big part of HR departments. Instead of simply depending on hunch, HR analytics helps in ascertaining the exact training needs for employees, which eventually adds value to individuals and benefits the organisation. The Future of HR Analytics HR analytics is an evidence-based approach for improving individual and organizational performance by making better decisions on the people side of the business. HR analytics can certainly enhance the credibility of the HR function by improving the effectiveness of HR policies and practices and contributing to the competitive advantage of organizations that develop it as a core competency. As such, HR professionals develop new skills and capabilities so that they can effectively partner with and lead IT and finance on HR analytics initiatives, HR professionals will need to address ethical dilemmas. RESULTS The present research aimed for an exploration of existing literature with the aim of understanding the relationship between human resource and analytics and understand the role it plays in the improvement of the existing range of managerial and HR related research. The study’s focus was on investigating on the future of HR analytics if integrated into the company to assist managers in predictive decision-making based on statistical evidences and relevant HR analytical data and literature. Also, the focus was on examining the IT infrastructure and technological interventions, including those that affect the way data is mined stored and made in terms of the effective implementation of HR analytics and the need for them in order to be efficient in terms of data storing in order to be relevant for HR analytics. CONCLUSIONS 203

To play a more relevant and strategic role in the organization, the HR function needs to move beyond mere reporting to accurate prediction. Instead of just generating reactive reports, it needs to embrace advanced analytics and predictive techniques that support strategic organizational goals. Application of predictive analytics in HR entails utilizing relevant data to solve specific business problems. The insights derived can help improve business performance as well as employee engagement and satisfaction. REFERENCES 1) Angrave, D., Charlwood, A., Kirkpatrick, I., Lawrence, M., & Stuart, M. 2016. HR and analytics: why HR are set to fail the big data challenge. Human Resource Management Journal, 26(1), pp1-11 2)Anon. People analytics (HR analytics). Retrieved February 26, 2018, from http://searchhrsoftware.techtarget.com/definition/human-resources-analytics-talentanalytics 3) Armstrong, M., & Taylor, S. 2014. Armstrong's handbook of human resource management practice. Kogan Page Publishers. 4) Bharti, A. 2017. Human resource analytics. South Asian Journal of Marketing & Management Research, 7 5), pp 68-77. [5] Fairhurst, P. 2014. Big data and HR analytics. Institute for Employment studies. 6) Ballinger, G. A., Cross, R., & Holtom, B. C. 2016. The right friends in the right places: Understanding network structure as a predictor of voluntary turnover. Journal of Applied Psychology, 101(4), pp 535–548. doi:10.1037/apl0000061 7)Briner, R. B., Denyer, D., & Rousseau, D. M. (2009). Evidence-Based Management: Concept Cleanup Time? 8) CAHRS Topical Working Groups (2011).State of HR Analytics: Facts and Findings, Cornell University 9) Harris, J. G., Craig, E., & Light, D. A. (2010). The New Generation of Human Capital Analytics. 10)Priyameet KaurKeer(2018) HR Analytics- New Career Option, p.g 07, The Hitavada, Newspaper, Nagpur Edition. 204

An Empirical Study on Influence of Motivational Practices on Motivation of Employees Authors: Dr. A.R. Sainath, Professor, Department of Management Studies, New Horizon College of Engineering, Bangalore, Karnataka. E-mail: [email protected], Mobile No: 9986559798 Mr. Rejoice Thomas, Ph.D -Research Scholar, Bangalore, Karnataka. E-mail: [email protected] Mobile No:9901646457 Abstract Information Technology (IT) industry is one of the fastest growing industries in India. It’s employees have contributed a great deal to the success story. Motivation is the driving force behind the quality output. The present paper attempts to understand the influence of motivational practices in IT industry in the city of Bangalore and the demographic variables, namely the gender and marital status of the employees. 510 software employees from 36IT companies are interviewed with a structured interview schedule. The data was analyzed using SPSS 17.0 statistical software. Descriptive statistics, Bivariate analysis, Multivariate analysis is used among other tools. The Cronbach’s Alpha Reliability test for finding out the reliability of the scale is adopted. Among other things, the study finds that the motivational practice Safety & Grievance Handling is not significant and not influencing the motivation of the male IT employees and the motivational practice namely, Employee - Employee Relationship & Friends / Relatives View of the Job is not InsfiogrnmifaictiaonnceTeacnhdnnoolot giyn(fIlTu)enisciinngvotlhveedmwotiitvhattihoen aorfetahseofef mhualmeaInT aenmdploorygeaensi.zational problem- solving through the design, development, and use of technology. Information Technology inKdueystwryorisdso:nMe ootfivtahteiofnaasltePsrtagctriocwesi,nMg iontdivuasttiroine,sIiTn eInmdpilao.yTehese, IDndemiaongIrTapinhdicusVtaryriahbalsescarved a name for itself in the international scenario as well. In India, it consists of the software industry and information technology enabled services (ITES) which also includes business process outsourcing (BPO) industry. WKheayt wMoortdisv:aItniofonrAmcattuioanllyTiesc?hnology, (IT) Professionals, Motivation, Practices Before getting into the Motivational practices, it is important to have an fair idea of what Motivation is? The term ’motivation’ is derived from the Latin word ‘movere’ which means to move. Motivation is the process that accounts for an individual’s intensity, direction, and persistence of efforts toward attaining a goal, specifically for Organizational Behaviour, toward attaining organizational goal. Intensity is how hard a person tries to meet the goal, Direction is the effort channelized towards organizational goals and Persistence is how long a person maintains effort towards a goal. It is important, as it supports business to achieve its goals in the most efficient and effective manner. In an organizations language, motivation is functionally described as the drive that pushes an individual to work. A motivated person is one who has a yearning to work. Both workers and employers are eager to understand the subject matter of motivation. If employees would be aware of the strengths and weaknesses that are related with work motivation, they could choose proper approach and carry out more successfully to seek most favorable satisfaction in their jobs. Employers are very much 205

concerned to know the nature, degree, and different type of motivation of their employees in order to be more capable, resourceful and fruitful. Survey of Literature: Benton (1998) relates the important function between organization and motivation. Organization refers to employees as “resources” or “assets”, meaning that employees are precious and profit making parts of a business organization. Among others, the study finds that the “Employers are apprehensive with their employees’ own motivation because they sturdily believe that motivation affects productivity at work”. Guay et al, (2010) stated that the notion of intrinsic motivation is closely related to intrinsic value. Intrinsic motivation refers to motivation which is animated by personal enjoyment, interest, or pleasure, and is usually contrasted with extrinsic motivation, which is manipulated by reinforcement contingencies.Antikainen et al. (2010) argued that once managers and leaders can help their employees to identify factors that make them to work with the firm, they will be able to make them feel motivated to work hard and carry out the assigned tasks with their best effort.Goncharuk & Monat (2009) concluded that managers and leaders in all types of organisations, including those in the IT sector must first help their workers to identify their interests with the company in order to motivate them. Gill & Mathur (2007) are of the opinion that when compared to small and medium sized firms, most large firms appear to have a more professional human resource management system to motivate workers to work with their best efforts or to retain them. Bjerke et al., (2007) concluded that in the context of management, motivation is very important to the organizational performance. As compared to other subjects, motivation is viewed differently in the context of human resource management. From this perspective, it is revealed that motivation is not possible. This is because we cannot motivate other persons, but what can be done is to influence what they are. Gill (2007) stated that incentive motivation is one of the most popular tools to get workers to do what managers want. Many scholars refer incentive motivation as 'dangling a carrot'. Shanks (2007) however argues that ‘while rewards may serve as incentives and those who bestow rewards may seek to use them as motivators, the real motivation to act comes from within the individual’. Statement of the Problem: In the fast changing scenario, it is important to know what motivational practices are practiced in the IT industry. Some of the researchable questions include whether the practices of motivation as suggested by Maslow, Vroom’s, Adam’s, Herzberg and others are relevant to IT industry now or not? What IT companies are doing to motivate their employees and how the employees are reacting to these motivational practices? Is there any influence of motivational practices of IT companies on the motivation of their employees (software engineers) ? It is in this context that the present study is under-taken. This research paper will give feedback on existing motivational practices and also throws light on the influence of these motivational practices on the motivation of employees with particular reference to their gender and their marital status. 206

Objective of the study: The research paper aims to study primarily, the 1. Influence of motivational practices on the motivation of employees with particular reference to the Gender of the IT employees and the, 2. Influence of motivational practices on the motivation of employees with particular reference to the Marital status of the IT employees. Methodology: The study covers the motivational practices of IT companies in the city of Bangalore and its influence on IT employees. The study includes 14 Multinational companies, 6 Indian large companies and 16 Indian medium & small companies. A total of 36 companies are covered in the study. Stratified random sampling technique is adopted for the study. The sample size of companies is about 20 %. 510 is the total sample size of IT employees. 45% are employed in MNC’s, 40% are by Indian large IT companies and 15% are by Indian small and medium IT companies. a.Data collection: A plan was drawn to collect the different motivational practices followed in the IT industry with the help of an interview schedule. The researcher had discussions with the Human Resources team of the companies and collected different motivational practices followed by them. All the practices were collected and tabulated. 97 statements were developed. A panel of 30 experts comprising of management teachers, researchers and industry practitioners having an average experience of minimum 12 years was prepared. Statements selected by more than 20 experts were accepted for the scale. The final form of the scale consisted of 57 statements. Motivational practices are grouped into 7 categories namely: 1. Clean Work Place, Autonomy & Promotion, 2. Safety & Grievance Handling, 3. Reputation for Job, Decision making & Training, 4. Manager - Subordinate relationship, Fringe benefits & Job security, 5. Employee - Employee Relationship & Friends / Relatives View of the Job, 6. Work Life Balance & Intrinsic Motivation, 7. Pay & Income. Further, each category included statements. 9 statements were made under the Clean Work Place, Autonomy & Promotion, 5 under Safety & Grievance Handling, 7 under Reputation for Job, Decision making & Training, 12 for Manager - Subordinate relationship, Fringe benefits & Job security, 6 for Employee - Employee Relationship & Friends / Relatives View of the Job, 9 for Work Life Balance & Intrinsic Motivation and 9 statements for Pay & Income. A five point scale was adopted to measure the extent of agreement/dis-agreement to these statements. 1 point was assigned for Strongly Disagree, 2 for Disagree, 3 for Neither Agree/Disagree, 4 for Agree and 5 =for Strongly Agree. 207

b.Tools of data analysis: Data was analyzed using SPSS 17.0 statistical software. The statistical techniques adopted are descriptive statistics (frequency, means, standard deviation and percentages), bivariate analysis i.e. Pearson correlation measures the strength of the associations between variables and multivariate analysis i.e. stepwise regression analysis in this study is adopted to predict one variable by other variables. The Cronbach’s Alpha reliability test for finding out the reliability of the scales is adopted for the study. Regression analysis is used for finding out the association of a particular motivational practice on the gender and marital status of the IT employees. The test of significance has been additionally employed to recognize the variables, which are significant. An attempt has been made to capture the motivational practices which can motivate the IT employees. Influence of Motivational Practices on motivation in relation to Gender and Marital Status of the IT employees: The study covers the influence of 7 motivational practices discussed above with two demographic variables namely the Gender and the Marital status of the IT employees: Table-1 Influence of Motivational Practices on Motivation in relation to Gender of IT Employees MALE FEMALE Motivational Practices Standardized Standardized Sig. Coefficients Sig. Coefficients Beta Beta (Constant) 0.000 0.000 Clean Work Place, Autonomy & Promotion 0.160 0.000 0.501 0.000 Safety & Grievance Handling -0.008 0.827 0.177 0.001 Reputation for Job, Decision Making & 0.157 0.000 0.068 0.158 Training Manager - Subordinate Relationship, 0.305 0.000 0.072 0.165 Fringe Benefits & Job Security Employee - Employee Relationship & 0.166 0.000 0.000 0.988 Friends / Relatives View of the Job Work Life Balance & Intrinsic Motivation 0.233 0.000 0.116 0.043 Pay & Income 0.308 0.000 0.376 0.000 Regression analysis is done on 269 male and on 241 female IT employees on the practices which influence motivation of IT employees. From the above table, It is found that all the motivational practices namely Clean Work Place, Autonomy & Promotion, Reputation for Job, Decision Making & Training, Manager - Subordinate Relationship, Fringe Benefits & Job Security, Employee - Employee Relationship & Friends / Relatives View of the Job, Work Life Balance & Intrinsic Motivation and Pay & Income is significant and will influence the motivation of the male IT employees. The motivational practice namely, Safety & Grievance Handling with a p-value of .827 is not significant and is therefore not influencing the 208

motivation of the male IT employees. Among the female IT employees, it can be seen that motivational practices namely Clean Work Place, Autonomy & Promotion, Safety & Grievance Handling, Work Life Balance & Intrinsic Motivation and Pay & Income with the p-value < 0.05 indicates significance and will influence the motivation of the female IT employees. The motivational practice Employee - Employee Relationship & Friends / Relatives View of the Job with a p- value of 0.988 is not significant and is not influencing motivation of the female IT employees. Table-2 Influence of Motivational Practices on Motivation in relation to Marital Status of IT Employees UN-MARRIED MARRIED Motivational Practices Standardized Standardized Coefficients Sig Coefficients Sig Beta Beta (Constant) 0.000 0.000 Clean Work Place, Autonomy & 0.223 0.000 0.262 0.000 Promotion Safety & Grievance Handling 0.108 0.006 0.170 0.000 Reputation for Job, Decision Making & 0.190 0.000 0.129 0.000 Training Manager - Subordinate Relationship, 0.242 0.000 0.321 0.000 Fringe Benefits & Job Security Employee - Employee Relationship & 0.144 0.000 0.153 0.000 Friends / Relatives View of the Job Work Life Balance & Intrinsic 0.213 0.000 0.218 0.000 Motivation Pay & Income 0.243 0.000 0.366 0.000 Regression analysis is done on 234 unmarried IT employees and 276 married IT employees for the practices which influences motivation. From the above table it can be seen that all the motivational practices namely Clean Work Place, Autonomy & Promotion Safety & Grievance Handling, Reputation for Job, Decision Making & Training, Manager - Subordinate Relationship, Fringe Benefits & Job Security, Employee - Employee Relationship & Friends / Relatives View of the Job, Work Life Balance & Intrinsic Motivation and Pay & Income having a p-value < 0.05 indicate significance and therefore influence the motivation of both married and the un- married IT employees. Major findings of the study: Among others, the study finds that: 1.Motivational practices namely Clean Work Place, Autonomy & Promotion, Reputation for Job, Decision Making & Training, Manager - Subordinate Relationship, Fringe Benefits & Job Security, Employee - Employee Relationship & Friends / Relatives View of the Job, Work Life Balance & Intrinsic Motivation and Pay & Income is influencing the motivation of male IT 209

employees. 2.Safety & Grievance Handling with a p-value of .827 is not influencing the motivation of the male IT employees. 3.Motivational practices namely Clean Work Place, Autonomy & Promotion, Safety & Grievance Handling, Work Life Balance & Intrinsic Motivation and Pay & Income with a p-value < 0.05 are influencing the motivation of the female IT employees. 4.Employee - Employee Relationship & Friends / Relatives View of the Job with a p- value of 0.988 is not influencing the motivation of the female IT employees. 5.All the motivational practices are having a p-value < 0.05 and are influencing the motivation of both the married and the un-married IT employees. To conclude, Most of the motivational practices practiced by the IT companies and matching with what is expected by the IT employees. Motivational practice namely, Safety & Grievance Handling is not influencing the motivation of the male IT employees and Employee - Employee Relationship & Friends / Relatives View is not influencing the motivation of the female IT employees. Both married and unmarried IT employees are motivated by all the motivational practices. If Safety& Grievance Handling and Employee - Employee Relationship and Friends / Relatives View of the Job is taken care by the IT Companies , there will be increased motivation among the IT employees. References: 1. Adair, John Effective Motivation: How to Get the Best Results from Everyone. Revised Ed.UK: Pan Macmillan, (2013). 2. Arnold, J. Work Psychology: Understanding Human Behaviour in the Workplace,(4th ed.). London: Prentice Hall Financial Times. (2005). 3. Atkinson, J.W. & Feather, N.T. eds. A theory of achievement motion. New York: Wiley. (1966). 4. Bjerke, R., Ind, N. & Paoli, D. The impact of aesthetics on employee satisfaction and motivation, Euro Med Journal of Business, vol. 2, no. 1, p. 57-73. (2007). 5. Boeree, C. George. Abraham Maslow. Biography. (2006). Retrieved October 6, 2008, from http://webspace.ship.edu/cgboer/Maslow.html 6. Bratton, J. & Gold, J. Human Resource Management: Theory and Practice, London: Palgrave Macmillan. (2007). 7. Gill, A. 'O2 makes work a rewarding experience:How to update rewards to match employee needs, Strategic HR Review, vol. 6, (2007). 8. Gill, A. & Mathur, N. 'Improving employee dedication and pro-social behavior', International Journal of Contemporary Hospitality Management, vol. 19, (2007). 9. Goncharuk, A.G. and Monat, J.P., A synergistic performance management model conjoining benchmarking and motivation,Benchmarking: An International Journal, Vol. 16, (2009). 10. Guay, F., Chanal, J., Ratelle, C. F., Marsh, H. W., Larose, S., & Boivin, M. Intrinsic, identified, and controlled types of motivation for school subjects in young elementary school children. British Journal of Educational Psychology, 80 (4), (2010). 11. Goncharuk, A.G. and Monat, J.P., A synergistic performance management model conjoining benchmarking and motivation, Benchmarking: An International Journal, 210

Vol. 16, (2009). 12. Nizami, Nausheen & Prasad, Narayan Decent Work: Insights from India's IT Industry. California: Sage Publications, (2013) 13. Shanks, N. H. Management and Motivation. In Introduction to Healthcare Management. Pub: Jones & Bartlett Learning, United States. (2007). 14. Silverstein, B. Motivating employees: Best practice. London: Collins Best Practices. (2007). Google Scholar Links of Faculty Members Details of Google Scholar ID Link ORCID No. Sl. Name of the Faculty Designation Google Scholar ID Link with NHCE Affiliation No Professor & HoD https://scholar.google.co.in/citations?user=VGolElkAAAAJ&hl=en 1 Dr.Sheelan Misra 2 Dr.A.R .Sainath Professor https://scholar.google.com/citations?hl=en&user=aFiD7-EAAAAJ 3 Dr.Priyameet Kaur Keer Associate Professor https://scholar.google.com/citations?user=nT02bm4AAAAJ&hl=en 4 Dr.Krishna Kumar Associate Professor https://scholar.google.com/citations?view_op=new_profile&hl=en 5 Santosh Kumar S Sr. Assistant Professor https://scholar.google.com/citations?user=aaJ4VdwAAAAJ&hl=en 6 Lokesh k n Sr. Assistant Professor https://scholar.google.com/citations?user=-k2cgV4AAAAJ&hl=en 7 Sheshu Sr. Assistant Professor https://scholar.google.com/citations?user=kmcbuFwAAAAJ&hl=en 8 Pavithra S Assistant Professor https://scholar.google.com/citations?user=esRwfQgAAAAJ&hl=en 9 Jayashree. N Assistant Professor https://scholar.google.com/citations?user=_yxrL1EAAAAJ&hl=en 10 Saumi Roy Assistant Professor https://scholar.google.com/citations?user=APLc0oEAAAAJ&hl=en Faculty Members Vidwan ID Details Sl. Name of the Faculty Designation Vidwan ID No 175333 1 Dr.Sheelan Misra Professor & HoD 175328 175455 2 Dr.A.R .Sainath Professor 204100 3 Dr.Priyameet Kaur Keer Associate Professor 169483 4 Dr.Krishna Kumar Associate Professor 5 Santosh Kumar S Sr. Assistant Professor 211

6 Lokesh k n Sr. Assistant Professor 183247 7 Sheshu Sr. Assistant Professor 43710 8 Pavithra S Assistant Professor (2) 180046 9 Jayashree. N Assistant Professor (2) 11843. 10 Saumi Roy Assistant Professor (1) 180043 212

Faculty Members Orcid ID Details Sl. Name of the Faculty Designation ORCID No. with NHCE Affiliation No Professor & HoD 0000-0001-8961-3329 1 Dr.Sheelan Misra 2 Dr.A.R .Sainath Professor 0000-0001-5017-0380 Associate Professor 0000-0002-4196-5170 Dr.Priyameet Kaur 3 Keer 4 Dr.Krishna Kumar Associate Professor 0000-0003-0950-0792 5 Santosh Kumar S Sr. Assistant Professor 0000-0002-2527-8100 6 Lokesh k n Sr. Assistant Professor 0000-0001-8867-2167 7 Sheshu Sr. Assistant Professor 0000-0003-3572-1599 8 Pavithra S Assistant Professor (2) 0000-0001-6106-3214 9 Jayashree. N Assistant Professor (2) 0000-0003-2850-8917 10 Saumi Roy Assistant Professor (1) 0000-0001-9327-573X Memorandum of Understanding Sl. Organisation with which MoU is Signed Name of Year of Duration List the Actual Number of No. the Signing Activities Under each Students/ Institution/ MoU MOU Year Wise Teachers Industry/ Participated Corporate 2020 Under MoUs House MoU Signed between NHCE & Harvard Business 2020 Global and NHCE professionals 1 School at Conference Room for conducting Value Ongoing Business analytics students of added programme for Global/Professional NHCE Ongoing MBA Guest Lecture, MBA students students Ongoing Webinars for both the For 1 batches 2 Incubation Agreement signed between NHCE & year Online part-time jobs, KOMOP Technology Pvt. Ltd. Internships, Training, MBA students Ongoing Workshops, Hackathon for both the MoU signed between NHCE and Connect-KX NHCE 2020 and International batches 3 GmbH (European Center for Knowledge Complete placements d For Mba Exchange) Certifications on Students And Embracing Change Faculties 4 MoU signed between NHCE & Harappa Learning NHCE 2020 Pvt. Ltd. Certifications on 1) 180 students of strategy and 2020-21 batch 5 MOU withIIMBx Academic Partnership NHCE 2020 sustainable enterprises Agreement (Renewed) 2) organizational design 30 Research : creating competitive Papers Are 6 MOU with International Journal Of Scientific NHCE 2020 advantage Published In Research In Science, Engineering, Technology The AICTE E Proceedings CONFERENCE 213

7 MOU with International Journal of Research & NHCE 2019 Complete International conference 30 faculties Analytical Reviews NHCE d paper published 8 MOU with Fintech Infosystems Pvt. Ltd. 2019 36 trading and learning MBA Finance months resources for learners Students virtual simulation 9 MOU with Trackinvest NHCE 2019 Ongoing platform activities, MBA Finance trading , investments Students etc. MOU with Confederation of Indian Micro, Small MBA Students 10 and Medium Enterprises (CIMSME i.e Clause NHCE 2019 Ongoing Guest lecture, Submit for both the 4.33 of the Deed) and Centre of Excellence for NHCE batches, MBA Innovation Incubation and Entrepreneurship faculties 11 MOU with capstone business stimulation - 2018 Ongoing Business stimulation 90 certification programme capstone classes 60 Faculties 12 MOU with ACADEMIC RESEARCH NHCE 2018 Complete International conference members CONFERENCES d published their research papers., 13 MOU with DAFFODIL INTERNATIONAL NHCE 2018 5 years Guest lecture, ED 180 students of UNIVERSITY-BANGLADESH Submit 2019-20 batch, 10 faculties Certifications on 1) strategy and 14 MOU with IIMBx B-School Partnership NHCE 2018 Ongoing sustainable enterprises 180 students of programme 2) organizational design 2019-20 batch : creating competitive advantage 15 MOU with MTC Global Centre of Excellence NHCE 2018 Ongoing Guest lecture, ED 180 students of Submit 2019-20 batch, 10 faculties 16 MOU with Association of women NHCE 2017 3 years Developing the skills of students and women entrepreneurs faculties of NHCE Workshop, guest 17 MOU with MTC Global Centre of Excellence- NHCE 2017 5 years lectures, industry MBA students Student Membership sessions , certification of all the batch programme Online part-time jobs, 18 MOU with VMEDU Targeting Success NHCE 2017 2 years Internships, Training, MBA students Workshops, Hackathon of all the batch and International placements 19 MOU with Yuri Gagarin Statre technical University NHCE 2016 5 years Academic and cultural nil of Saratov , Russia exchanges 20 MOU with BCP Associates NHCE 2015 1 year Labour law compliance MBA -HR management STUDENTS 214

Awards and Recognition Name of the Faculty Name of the award Year of Awarding Agency Award Dr. Priyameet Kaur Keer Most Influential Women in 2020 AMA ACADEMY, NINJA Dr. A R Sainath Academics-2020 2020 GROUP, HYDERABAD. Best Paper Presentation awarded NHCE Mr. Santosh Kumar S in AICTE sponsored One week 2019 Dr. Sheelan Misra National E-Conference 2018 NHCE Dr. A R Sainath Best Paper award in International 2018 MTC GLOBAL Conference Dec-2019 MTC GLOBAL MTC Global Best Teacher at World Edu Summit 2018 MTC Global Best Teacher at World Edu Summit 2018 Award Details Name of Nature of Award/ Event Host/ Agency Organisation Year Mobile Faculty Recognition Member Fermata Fermata LCM 2020 9900911649 Invited as a Panellist: 2020 9900911649 Dr. Sheelan What Next!!! Are you Antwak Bangalore 2020 9900911649 Misra prepared for a Tilt INDIA #1 2020 9900911649 successful CAREER Post AICTE Bangalore 2020 9986559798 Dr. Sheelan Covid 19? Are you able New Horizon College Misra to manage your stress of Engineering AICTE Dr. Sheelan during Covid 19? New Horizon Misra Invited as Expert for College of Collaboration Engineering Dr. Sheelan Excellence Talks - a Misra master class experience on the topic Dr. A R Sainath \"Transformational Leadership\" Participated in AICTE- FDP Best Paper Presentation awarded in AICTE sponsored One week National E- Conference Dr. Priyameet Most Influential Academy of AMP and 2020 9663844004 Kaur Keer Women in Academics- Management Education Ninja 2020 Professional (AMP) Group, Hyderabad. and Education Ninja Group, Hyderabad. 215

Dr. Priyameet Participated in AICTE- AICTE AICTE NIL 9663844004 Kaur Keer FDP ICIREMS-2019 NHCE 2019 9964377796 Best Paper award in Mr. Santosh International Kumar S Conference Dec-2019 Mr. Santosh Scored 70% in National Muthurangam Govt. Muthurangam 2019 9964377796 Kumar S level e-Quiz Arts College, Vellore Govt. Arts College, competition on Vellore \"Research Aptitude\" Mr. Santosh GCU ALPHA WEBNINAR GARDEN CITY GARDEN CITY 2020 9964377796 Kumar S UNIVERSITY UNIVERSITY Nil 9945586671 2020 9945586671 Ms. Saumi Roy Scored 80% in National Govt. Shyama Prasad Govt. Shyama Level online short E- Mukharjee College, Prasad Mukharjee Ms. Saumi Roy Quiz on \"English Chhattisgarh College, Grammar and English Chhattisgarh Literature Arignar Anna Government Arts Arignar Anna Scored 100% in Quiz on College, Attur Government Arts 5 Day FDP College, Attur Ms. Pavithra S GCU Alpha Webninar Garden City Garden City 2020 9844964637 University University Nil 9740516753 Ms. Jayashree Participated in AICTE- International Online Meerut University NIL 8095550098 N, FDP quiz , Meerut Mr. Lokesh AICTE AICTE R&D Facilities of the Department 1. Lecture Halls: The lecture halls are airy, spacious and well ventilated in conformity with international standards. Extensive use of audio-visual media enables the students to grasp advance technology quite easily. 2. Seminar Hall: The Seminar Hall is utilized for conducting Departmental events like seminars, workshops, guest lecturers and various other academic activities. 3. Departmental Library: The department has a spacious library which provides students with ample of books and space to read, Study and discuss. 4. MBA Conference Room: The conference room is utilized for holding Industry – Academic interaction 5. MBA Discussion Room: Well-equipped discussion room is used for group discussion, mock interviews, planning & organizing events & activities. 6. Well Equipped centre for Incubation. 7. Discussion Room for Entrepreneurial Activities. 216

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TIME ZONES TRENDS & TECHNOLOGY TIMELINE 2010+ Pe A roadmap for the exploration of current & future trends ZONE 1: 2010-2015 (+ some predictions to stir things up. More at nowandnext.com) ZONE 2: 2015-2020 ZONE 3: 2020-2025 Convergence of healthcare Contents of British Library available on a postage stamp-sized chip ZONE 4: 2025-2035 and financial planning Digital cash widely embedded in clothing ZONE 5: 2035-2050 Digital cash Single global Animals suing humans Baby licences Growth of ‘Tech-No’ movement Desire for control Notes on time travel widely e-currency Global population hits 9 billion This map is a broad representation of some of embedded in Most people Online funerals Search for meaning Digital cele the trends and technologies currently visible. human body have multiple (Mondays to Fridays only) Provenance Improvement works are carried out at weekends and travellers should check to see whether lines are still Brain drain from hedge funds to scientific R&D (energy #1 priority) presences operable before commencing any journeys. Helpful suggestions concerning new routes and excursions Wealth asylum seekers Food passports 10-mile diets Convenience Well-being are always welcome. Calorie taxes If you wish to travel outside of Zone 1 you are advised to bring comfy shoes and a camera. Travellers are also Indulgence Authenticity Rise of N11 countries advised to bring their own supplies of food and water although weapons are unnecessary if you keep to well Whole life financial planning linked Rising levels of autocracy trodden paths. Also note that travel into Zone 5 is not to whole family model available for people aged over 75 years of age. First Internet court Growth of Business sustainability Growth of bartering Government Growth of Online communities micro-insurance largest determinant of Emergence of Gross A3 and A2 Prints of this map start physical stock price 75-year mortgages Pre-pay currency cards Power shift e-services Happiness metrics communities Genetically Eastwards Full colour prints of this map are available enhanced pets Emergence of to anyone that asks nicely. A small charge is Retirement Gross National Micro-finance Sp levied to cover print and postage costs only. Contact< [email protected] >stating Move to global pricing Happiness Monolines whether you’d like A3 or A2 size and saying of consumer goods metrics which country the map is to be delivered to. (driven by shopbots) Delivery is available to anywhere in the world. Figurative Last CD is Widespread cuts in Atternatively, just print this out yourself revolution in the published public services ( A3 minimum recommended ) e-ink comes Paper statements & bills Free-tailing arts as Face recognition Sourced neoclassicism Bionic of age A graphic novel Conspicuous non-consumption wo Olympics wins the Booker Infrastructure under Material for this map has been soured from a returns Acute labour Synthetic biology number of publications including Future Files Just-in-time Prize shortages in Life story labelling Urbanisat and What’s Next aged-care sector shopping www.futuretrendsbook.com Too much choice Blurring of sectors Sensory experiences www.nowandnext.com Disappearance Robocops in Local shopping Device convergence Price polarisation Loc of checkouts shopping malls Virtual libraries (High / Low ) Acknowledgements Blurring of scientific disciplines Increasing interest rates Stored This map was conceived and created by Richard Online micro-p Watson at Nowandnext.com with some help from Pets outnumber people globally Malicious intent detectors Benjamin Frazer at Snap. Also thanks to Oliver Growth of security Micro-finan Freeman, Mike Jackson and Scott Martin. Robot population Digital mirrors Basic forms of AI algorithms surpasses human This map is published under a creative Commons 2.5 High Street Internet addiction clinic Mind control toys Personalisation Use of fake information Share-A-Like licence. This basically means that you can population as a weapon do whatever you like with this map just so long as you say where it came from. Average lifespan Unexpected increase Death of distance Health & safety hysteria Information pandemics M 100 years in fertility rates Home /work convergence Basic forms of AI Web 2.0 Volatility Home swap holidays Societal feminisation Empathy ‘Spinning disk’ Cloud storage Simplicit memory devices Full concentration Machines that can judge emotional state of user T Devices re-programming themselves Increasing regulation 25% of company & compliance HQs now virtual Widespread use of brain Single person households Tightening security in light of experience Contactless pay scans in job interviews Online video Micro-blogging Digitalisation Digital diets Constant digital Prediction markets Telepresence Virtua distraction Physical newspapers Near extinction of quality journalism Growth in passenger numbers Online medical records Green IT become luxury items spawns philanthropic funding Domestic tourism Childcare robots Voluntourism Face recognition doors Quiet paint Sustaina4 billion mobile Wireless re-charge Holographic storage phone subscribers Intelligent packaging Fair trade Medical tourism Cyber-pet vets Video wallpaper Aged care robots Wind power Low-cost competition Shifting centres of economic activity Green cities Space tourism Outsourcing backlash Dining Rooms Computers with Modesty Consumer e-health Slow food Cautious optimi moving parts Verbal search Green buildings Sustainable tourism Comfort foods CHIM Ocean dead zones Ubiquitous computing Affective computing Nano - solar Global hospital brands Eco-cynics Gen X start to outlive their offspring End of low-cos Most peopl Augmented reality Phone spam Fuel-cell phones Human organ farms Skills sh contact lenses Wearable computers Resources increasingly acquired on a no questions asked basis DNA Global sensor network Urban (vertical) farming Male birth control pill Digital n computing Focus on hardware reduces as Plastic bones Artific services more distributed and Rise of the vegetarians Creation of new interoperable arable lands as planet Declining water quality Quantum computing warms up No more anonymous email addresses Peak water Genetic diets Privacy All babies implanted with GPS & ID chips (one email address per person) Global migration drift to warming parts of Food allergies eliminated the northern hemisphere Russia Space solar power Individual energy/carbon monitoring leads to allowances (demographically) Micro-scale health-b and/or tiered costing based on system akin to personal Meditation/holistic services bundled with medical pr Creation of Department of alcohol, firearms, soft drinks and confectionary Spray on s (mandatory health warnings on all alcohol, junk food and candy) Optimism about the future Global risks* V Commodity price spikes V Electricity shortages V Green energy bubble V Raw materials shortages V Rapid increase in cyber crime V Genetic terrorism * Low probability/high impact events that V Mass migration of population V Critical infrastructure attack V Collapse of US dollar V Nuclear terrorism V Rogue stakeholder V Global supply chain could derail any of the above trends and V Internet brownouts V WMD Proliferation V Terrorist attack on ur predictions

ersonal responsibility People renting dreams Community Compulsory LEGEND Printable TV screens theatre in the paternity tests Inheritance First child born in space Mega trend round takes Trend off (again) Prediction Dangerous currents Invisibility cloaks Prison ships Children become luxury objects Poor visibility First human clone e-voting in supermarkets Turkey, Iran and Mexico High-speed link Letter writing Disintegration of EU become key powers Partial ruin Folk-art revival Increased immigration Collapse of free trade Government PR budgets bPoumlsbes Hunger for shared experiences to solve skills crisis exceed military spending Culture of immediacy Cheques Widespread Resurgence of hobbies & craft 1/3 of all military vehicles Function based tariffs outbreaks now unmanned for electricity Pastism of panic Revival of far-right politics ebrities Rising rage Expecting less Virtual protests Growth of G2 Widespread use of nano-materials People able to record every event from birth to death Face recognition doors Nostalgia Bio-mimicry Airborne networks Shape shifting materials Molecular machines Fully sensory internet Cosmetic brain Green politics Increasing influence of surgery Traceability Regionality oil states on US politics World’sofpiresntsthinorIinudmiareactor Biotechnology Energy harvesting buildings Epidemic of new mental disorders Middle Class unrest Growth of virtual communities Open source intelligence gathering Virtual water Genetic prophesy at birth state control Carbon trading Globalisation unravelling Lunar dimming streetlights Intelligent vending machines linked to uncensored s National Men behaving like women use of digital devices peech recognition RFID Robotics Local energy transmission networks Artificial eyes Meltdown of global Ageing Shopping 2.0 Customer service avatars Womb based therapy financial system Small indulgences Third spaces Redefinition of health to become common place Negawatts Clean coal Rare earths include happiness/well-being Shift to local EDLP Authenticity Carbon chaos trade Investment in renewable energy Re-regulation Half the world now Increase in Brain gyms Growth of outsourcing omen behaving like men Increasing longevity living under double pigouvian taxes to Africa digit inflation Mercantilism r-investment Networked risk Broader definitions of health Home-based health Peak landfill tionNuclear power renaissance Pensions funding crisis Seasonality Obesity Consumer e-health Cities painted Medical tourism white to Globalisation increase reflectivity Declining fertility Anxiety calism Urban/rural divide Loneliness Growth of private Plastic bridges Metabolomics currencies d value cards Micro-power generation Home as refuge Peak Uranium Telemedicine iPills payments Domestic energy dashboards Modular spaces Identity theft Rising economc Driverless lorries Decline in real wages protectionism First moon hotel Industries consolidating globally Debt nce P2P lending Depression Debt Stress Islamic finance Personal nooks Payments to Pilotless Services outsourcing enter most cities airliners Mobile payments Sense of entitlement by private vehicle Peak copper Brain Victim culture Home/street holidays Healthcare rationing Shift to knowledge intensive industries Large screens level domestic waste ty Unsupervised adults everywhere immgaemrFsuiinvllgye processing All ads now T.I.M Robotic surgery secDuraittya Individualism Droughts Believers versus heretics personalised Flooding yments User filtering 30% of all books Hypersonic Binge drinking Bio - simulations User generated content now digital airliners Wilder weather Energy storage al currencies Growth of digital narcissism Shorter formats Real-time car insurance All televised sport now short format Emergence of green nationalism e-books Seabed mining Fuel-cell cars Face recognition rear view mirrors (linked to ignition) ability Environmental Gesture-based computing change Hybrid fuels Bio-fuel backlash 3-D teleconferences Collapse of Return of food inflation and food riots Chinese banking Fractional ownership system ism Urban car sharing Laboratory grown meat Rocbroopticpoinllsineacttisonfor Companies ME liquidity Increasing inflation in supermarkets re-think OHS&E 2-speed economies Increasing complexity Electricity shortages after Lunar dimming streetlights Fragrainncmeocbailretsridges workplace stress st inputs Water labelling claims All vehicles fitted with GPS Oil at $200 a barrel le have 2+ careers 80% of global energy requirements still met by oil /coal /gas Facebook vacations hortages bite Holidays at home packages (meet your online friends in person) Communication free resorts Augmented reality windscreens Sleep hotels Solar energy generating windows Open source explodes with global standard for royalty payments nomads Industrial repatriation Generational conflict in the workplace Increasing automation Water labelling Creative industries cial livers Hydrogen fuel stations of all products become dominant Variable road-pricing dependent on time of day/traffic volume Second asset contributors to bubble global GDP Oceanic thermal converters 80% of global population now obese Vehicles bought for technology upgrades rather than model changes Fusion reactors Average car now 50% of weight of 2010 model equivalent Cities laced with small vehicle lanes separate from road system bots Humility rocedures Self-driving cars Self-repairing roads Scarcity of hydrocarbon service First moon mine surgical gloves / fuel stations Intimacy DNA repair Bio-diversity Stringent laws requiring high levels of recyclability in all products e V US/China conflict V Global pandemic V Middle class revolution V Major nano-tech accident V Israel/Iran conflict V Conflict with North Korea V Collapse of China V Space weather disruption to comms r V Bisphenol A link to cancer V Political disintegration of Saudi Arabia V Mobile phone link to cancer V Aliens visit earth disruption V Geographical expansion of Russia V Systemic failure of financial system V Credit Default Swaps V Return of the Messiah rban water supply V Major earthquake in mega city V Fundamentalist takeover in Pakistan V Rogue asteroid V People taking trend maps too seriously