9th IFAC Conference on Manufacturing Modelling, Management and 9th IFAC Conference on Manufacturing Modelling, Management and Control 9th IFAC Conference on Manufacturing Modelling, Management and Control 9th IFAC Conference on Modelling, Management and Berlin, Germany, August 28-30, 2019 Available online at www.sciencedirect.com 9th IFAC Conference on Manufacturing Manufacturing Modelling, Management and Control Berlin, Germany, August 28-30, 2019 9th IFAC Conference on Manufacturing Modelling, Management and Control Control Berlin, Germany, August 28-30, 2019 Control Berlin, Germany, Germany, August 28-30, 28-30, 2019 Berlin, Berlin, Germany, August August 28-30, 2019 2019
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IFAC PapersOnLine 52-13 (2019) 2668–2673 Modelling Modelling the the industrial industrial workforce workforce dynamics dynamics and and exit exit in in the the ageing ageing society society Modelling the industrial workforce dynamics and exit in the ageing society Modelling the industrial workforce dynamics and exit in the ageing society Modelling workforce dynamics and exit in the ageing society Vlado Dimovski*, Barbara Grah**, Simon Colnar*** Modelling the the industrial industrial workforce dynamics and exit in the ageing society Vlado Dimovski*, Barbara Grah**, Simon Colnar***
Faculty of Economics, University ofSimon Ljubljana, Slovenia Vlado Dimovski*, Barbara Grah**, Colnar*** Faculty of Economics, University ofSimon Ljubljana, Slovenia Vlado Dimovski*, Barbara Grah**, Colnar*** Vlado Dimovski*, Barbara Grah**, Simon Colnar*** * (e-mail:
[email protected]) Faculty of Economics, University Ljubljana, Slovenia Vlado Dimovski*, Barbara Grah**,of Simon Colnar*** * (e-mail:
[email protected]) Faculty of Economics, University of Ljubljana, Slovenia Faculty Economics, University of Ljubljana, Slovenia (e-mail:
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[email protected]) Faculty of of Economics, University of Ljubljana, Slovenia **** (e-mail: ** (e-mail:
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[email protected]) Abstract: Abstract: Abstract: Workers are becoming the most important asset of organizations and economies. Ageing of population Abstract: Workers are becoming the most important asset of organizations and economies. Ageing of population Abstract: will decrease the availability of human resources in European economies. Understanding productivity of Workers are becoming the most important asset of organizations and economies. Ageing of population will decrease the availability of human resources in European economies. Understanding productivity of Workers are the important of organizations and economies. Ageing of Workers are becoming becoming the most most important asset of organizations and economies. economies. Ageing of population population different groups ofavailability workers isof important for asset organizations and national To stayproductivity competitive in Workers are becoming the most important asset of organizations and economies. Ageing of population will decrease the human resources in European economies. Understanding of different groups of workers is important for organizations and national economies. To stay competitive in will decrease the availability of human human resources resources in European European economies. Understanding productivity will decrease availability of in economies. Understanding productivity of the long termthe sustainable manufacturing workforce solutions are required. In the paper we presentof a will decrease the availability of human resources in European economies. Understanding productivity of different groups of workers is important for organizations and national economies. To stay competitive the long groups term sustainable manufacturing workforce solutions are required. In the paper we present in a different of workers is important for organizations and national economies. To stay competitive in multiple decrement model manufacturing ofimportant workforce transition from potential employee, employed trainee, fully different groups of workers is for organizations and national economies. To stay competitive in different groups of workers is important for organizations and national economies. To stay competitive in the long term sustainable workforce solutions are required. In the paper we present a multiple decrement model of workforce transition from potential employee, employed trainee, fully the long term sustainable manufacturing workforce solutions are required. In the paper we present the long term sustainable manufacturing solutions required. In the paper we present productive, partially productive, partiallyworkforce employedfrom to potential theirare exit in terms of unemployment andaaa the long term sustainable manufacturing workforce solutions are required. In the paper we present multiple decrement model of workforce transition employee, employed trainee, fully productive, partiallymodel productive, partiallytransition employedfrom to potential their exitemployee, in terms employed of unemployment and multiple decrement decrement of workforce trainee, fully fully retirement orpartially death. model The availability of workforce infrom national economy depends onunemployment the quality age multiple of transition potential employee, employed trainee, multiple decrement of workforce workforce transition potential employee, employed trainee,of productive, productive, partially employed to their exit in terms of and retirement orpartially death. model The availability of workforce infrom national economy depends onunemployment the quality offully age productive, productive, partially employed to their exit in terms of and management, where occupational safety and health of an ageing worker is a major consideration. Model productive, partially productive, partially employed to their exit in terms of unemployment and productive, partially productive, partially employed toageing theireconomy exit in isdepends terms ofon unemployment and retirement or death. The availability of workforce in national the quality of age management, where occupational safety and health of an worker a major consideration. Model retirement or death. The availability of workforce in national economy depends on the quality of age retirement or death. The availability workforce in national economy depends on the quality of age allows measuring the quality of safety theof organizational age management system, which has not Model been retirement or death. The availability of workforce in national economy depends on the quality of age management, where occupational and health of an ageing worker is a major consideration. allows measuring the quality of the organizational age management system, which has not been management, where occupational safety and health of an ageing worker is a major consideration. Model management, occupational safety and of an ageing worker is aa major consideration. Model developed yetwhere andthe shows howofthe optimal policy increasing working period andhasinfluence of management, occupational safety and health health of for an ageing worker issystem, major consideration. allows quality the organizational age management which not been developed yetwhere andthe shows howof policy for increasing working period andhas influence of allows measuring measuring the quality ofthe theoptimal organizational ageageing management system, which has not Model been allows measuring quality the organizational age management system, which not been investment in workplace solutions and education for the workforce increases their availability in allows measuring the quality of the organizational age management system, which has not been developed yet and shows how the optimal policy for increasing working period and influence investment in workplace solutions and education for the ageing workforce increases their availability in developed yet Paper and shows shows howa more the optimal optimal policy for increasing increasing working period and- mathematical influence of of developed yet and how the policy for working and influence of the long term. presents objective measuring tool,workforce based onincreases an period actuarial developed yet and shows how the optimal policy for increasing working period and influence of investment in workplace solutions and education for the ageing their availability in the long term. Paper presents a more objective measuring tool, based on an actuarial mathematical investment in workplace solutions and education for the ageing workforce increases their availability in investment in workplace solutions and education for the workforce increases their availability in method. Thus, the objective of the paper is to present howageing to tool, develop an actuarial model for determining investment in workplace solutions and education for the ageing workforce increases their availability in the long term. Paper presents a more objective measuring based on an actuarial mathematical method. Thus, the objective of the paperobjective is to present how to tool, develop an actuarial model for determining the long term. Paper presents a more measuring based on an actuarial mathematical quality of the age management different types ofhow organizations in the employment of EU the long term. Paper presents aa in more objective measuring tool, based on actuarial --system mathematical the long term. Paper presents more objective measuring tool, based on an an actuarial mathematical method. Thus, objective of paper is present to develop an actuarial model for determining the quality of the age management in different ofhow organizations in the employment system of EU method. Thus, the objective of the the paper is to to types present how to develop anpolicies actuarial model for determining method. Thus, objective of the paper is to present to develop an actuarial model for determining member states and how to evaluate the development of age management and other social policies method. Thus, the objective of thein paper is to types presentof how to develop in anpolicies actuarial model for determining the quality of age management different organizations the employment system of member states and how to evaluate the development age management and other social policies the quality of age management in different types of organizations in the employment system of EU EU the quality of age management different organizations the employment of EU for older workers. The paper alsoin presents a types modelof ofage collecting andin processing data in system the system of the quality of age management in different types of organizations in the employment system of EU member states and how to evaluate the development management policies and other social policies for older workers. The paper also presents a model of collecting and processing data in the system of member states and how to evaluate the development of age management policies and other social policies member states and how to evaluate the development of age management policies and other social policies statistical reports relevant for the Republic of Slovenia. Collected statistical data will enable better member states and relevant how to evaluate development ofof age management policies and other social policies for older workers. The paper presents aa of model collecting and processing data in the system of statistical reports foralso the the Republic Slovenia. Collected statistical data will enable better for older workers. The paper also presents model of collecting and processing data in the system of forecast ofworkers. workforce exit based on presents declining capacities of older workers. for older The paper also aafunctional model of collecting and processing data in the system of for older workers. The paper also presents model of collecting and processing data in the system of statistical reports relevant for the Republic of Slovenia. Collected statistical data will enable better forecast of workforce exit based on declining functional capacities of older workers. statistical reports relevant for the Republic of Slovenia. Collected statistical data will enable better statistical reports relevant for the the Republic functional of Slovenia. Slovenia. Collected statistical data will will enable enable better better statistical relevant for Republic of Collected statistical data forecast workforce exit on capacities of workers. forecast of ofreports workforce exit based based on declining declining functional capacities of older older workers. Keywords: age management, pension system, age-productivity, active ageing, retirement policy. forecast workforce exit on functional of workers. Keywords: management, pension system, age-productivity, active ageing, retirement policy. forecast of of age workforce exit based based on declining declining functional capacities capacities of older older workers. Keywords: age management, pension system, age-productivity, active ageing, retirement policy. © 2019, IFAC (International Federation ofmodelling Automatic Control) Hosting by Elsevier Ltd. rights reserved. Keywords: age management, pension system, age-productivity, active ageing, retirement policy. The authors acknowledge that the paper the workforce dynamics and exit All in the ageing society Keywords: management, system, age-productivity, active ageing, retirement policy. The authorsage acknowledge thatpension the paper modelling the workforce dynamics and exit in the ageing society Keywords: age management, pension system, age-productivity, active ageing, retirement policy. was financially supported by the Slovenian Research Agency, Program P5-0364 The Impact of The authors acknowledge that the paper modelling the workforce dynamics and exit in the ageing society was authors financially supportedthat bythe thepaper Slovenian Research Agency,dynamics Programand P5-0364 - The Impact of The acknowledge modelling the workforce exit in the ageing society Corporate Governance, Organizational Learning, and Knowledge Management on Modern Organization. The authors acknowledge that the paper modelling the workforce dynamics and exit in the ageing society The authors acknowledge that the paper modelling theKnowledge workforce dynamics and exit in the ageing society was financially supported by the Slovenian Research Agency, Program P5-0364 -- The Impact of Corporate Governance, Organizational Learning, and Management on Modern Organization. was financially supported by the Slovenian Research Agency, Program P5-0364 The Impact of was financially supported by Research Agency, Program -- The Impact was financially supported by the the Slovenian Slovenian Research Agency,Management Program P5-0364 P5-0364 The Impact of of Corporate Governance, Organizational Learning, and Knowledge on Modern Organization. Corporate Governance, Organizational Learning, and Knowledge Management on Modern Organization. Corporate Management on Modern Organization. Knowledge Corporate Governance, Governance, Organizational Organizational Learning, Learning, and and Knowledge Management on Modern Organization. of active ageing. Active ageing is defined by The World 1. INTRODUCTION of active ageing. Active ageing is defined by The World Health Organization in Zacher etisal.defined (2018,by p.37) asWorld “the 1. INTRODUCTION of active ageing. Active ageing The Health Organization in Zacher etis al.defined (2018,by p.37) asWorld “the active Active ageing The 1. of active ageing. Active ageing is defined The World process of ageing. optimizing opportunities for health,by participation, ToINTRODUCTION ensure sustainable and resilient production, national of 1. INTRODUCTION of active ageing. Active ageing is defined by The World Health Organization in Zacher et al. (2018, p.37) as “the 1. INTRODUCTION process of optimizing opportunities for health, participation, To ensure sustainable and resilient production, national Health Organization in Zacher et al. (2018, p.37) as “the 1. INTRODUCTION Health Organization Zacher al. (2018, “the and security in order in to enhance quality of p.37) life asas people economies need to assureand a sufficient number of industrial Health Organization Zacher et etthe (2018, “the process of optimizing opportunities for health, participation, To ensure sustainable resilient production, national and security in order in to enhance theal. quality of p.37) life asaspeople economies need to assureand a sufficient number of industrial process of optimizing opportunities for health, participation, To ensure sustainable resilient production, national age.” Organizations such as United Nations, Organization for To ensure sustainable and resilient production, national process of optimizing opportunities for health, participation, workers in their functional regions (Bogataj et al., 2017b). process of optimizing opportunities for health, participation, and security in order to enhance the quality of life as people To ensure sustainable and resilient production, national economies need to assure a sufficient number of industrial age.”security Organizations such as United Nations, Organization for workers in need their to functional regions (Bogataj et of al.,industrial 2017b). and in order to enhance the quality of life as people economies assure aaare sufficient number Economic Cooperation and Development and the European economies need to assure sufficient number of industrial and security in order to enhance the quality of life as people Nowadays people globally living longer. Regardless of security in ordersuch to and enhance theNations, qualityand of the life as people age.” Organizations as United Organization for economies need to assure aare sufficient numberet of industrial workers in their functional regions al., 2017b). Economic Cooperation Development European Nowadays people globally living(Bogataj longer. Regardless of and age.” Organizations as United Nations, Organization for workers in their functional regions (Bogataj et al., 2017b). age.” Organizations such as United Nations, Organization for Commission are alsosuch concerned in providing thethe society with workers in their functional regions (Bogataj et al., 2017b). their country of origin (i.e. United States, China or Slovenia) age.” Organizations such as United Nations, Organization for Economic Cooperation and Development and European workers in their functional regions (Bogataj et al., 2017b). Nowadays people globally are living longer. Regardless of Commission are also concerned in providing thethe society with their country of origin (i.e. United States, China or Slovenia) Economic Cooperation and Development and European Nowadays people globally are living longer. Regardless of a sustainable active ageing policy framework. The Europe Nowadays people globally are living longer. Regardless of Economic Cooperation and Development and the European the average human life expectancy has increased over the Economic Cooperation and Development and the European Commission are also concerned in providing the society with Nowadays people globally are living longer. Regardless of their country of origin (i.e. United States, China or Slovenia) a sustainable active ageing policy framework. The Europe the average human life(i.e. expectancy has increased over the Commission also concerned in providing the society their country of origin United China or Slovenia) are also concerned in providing the with 2020 strategyare is the agenda growth and jobs Europe forwith the their country of (i.e. United States, China or past few decades. Danson (2007)States, similarly argues that the all Commission Commission are alsoEU's concerned infor providing the society society aa2020 sustainable active ageing policy framework. The their country of origin origin (i.e. United States, China or Slovenia) Slovenia) the average human life expectancy has increased over strategy is the EU's agenda for growth and jobs forwith the past few decades. Danson (2007) similarly argues that all sustainable active ageing policy framework. The Europe the average human life expectancy has increased over the a sustainable active ageing policy framework. The Europe current decade. It emphasises smart, sustainable and inclusive the average human life expectancy has increased over the developed economies are already witnessing population a sustainable active ageing policy framework. The Europe 2020 strategy is the EU's agenda for growth and jobs for the the average human life expectancy has increased over the past few decades. Danson (2007) similarly argues that all current decade. It emphasises smart, sustainable and inclusive developed economies are already witnessing population 2020 strategy strategy is the the EU's agendathe forstructural growth and and jobs for for the the past few decades. (2007) similarly argues that is agenda for growth jobs growth as a way to EU's overcome weaknesses in past fewthat decades. Danson (2007) similarly argues that all all 2020 ageing, can be Danson explained with increased life expectancy 2020 strategy isIt the agenda forstructural growth and jobs for the current decade. emphasises smart, sustainable and inclusive past few decades. (2007) similarly argues that all developed economies are already witnessing population growth as a way to EU's overcome the weaknesses in ageing, that can be Danson explained with increased life expectancy current decade. It emphasises smart, sustainable and inclusive developed economies are already witnessing population current decade. It emphasises smart, sustainable and inclusive Europe's economy, improve its competitiveness and developed economies are already witnessing population and declining birth rates. As people are living longer they are current It emphasises smart, sustainable and inclusive growth as aa way to overcome the weaknesses in developed economies are already witnessing population ageing, that can be explained with increased life expectancy Europe'sdecade. economy, improve itsstructural competitiveness and and declining birth rates. As people are living longer they are growth as way to overcome the structural weaknesses in ageing, that can be explained with increased life expectancy productivity and to underpin a the sustainable social market ageing, that can be explained with increased life expectancy growth as aa way overcome structural weaknesses in also consequently working longer, which means they will growth as way to overcome the structural weaknesses in Europe's economy, improve its competitiveness and ageing, that can be explained with increased life expectancy and declining birth rates. As people are living longer they are productivity and underpin a sustainable social market also consequently working longer, which means they will Europe's economy, improve its competitiveness and and declining birth rates. As people are living longer they are Europe's economy, improve its competitiveness and economy. Europe 2020 strategy states as employment target: and declining birth rates. As people are living longer they are encounter changes related to their working lives and Europe's economy, improve its competitiveness and productivity and underpin a sustainable social market and declining birth rates. As people are living longer they are also consequently working longer, which means they will economy. Europe 2020 strategy states as employment target: encounter changesworking related longer, to their working lives and productivity and underpin social market also consequently which means they will and underpin sustainable social market “75% of Europe people aged 20–64aaa states tosustainable be asinemployment work” (European also consequently working longer, which means they professional careers, however only fewworking organizations and productivity productivity and 2020 underpin sustainable social market economy. strategy target: also consequently working longer, which means lives they will will encounter changes related to their and “75% of people aged 20–64 to be in work” (European professional careers, however only few organizations economy. Europe 2020 strategy states as employment target: encounter changes related to their working lives and economy. Europe 2020 strategy states as employment target: Commission, 2010). Many European member states are far encounter changes related to their working lives and national economies already acknowledged the opportunities economy. Europe 2020 strategy states as employment target: “75% of people aged 20–64 to be in work” (European encounter changes related to their working lives and professional careers, however only few organizations Commission, 2010). Many European member states are far national economies already acknowledged the opportunities “75% of people aged 20–64 to be in work” (European professional careers, however only few organizations and from achieving this target. Shrinking workforce as forecasted professional careers, however only few organizations and “75% of people aged 20–64 to be in work” (European and challenges that greater longevity brings (Gratton & Scott, “75% of people aged 20–64 to be in work” (European Commission, 2010). Many European member states are far professional careers, however only few organizations and national economies already acknowledged the opportunities from achieving this target. Shrinking workforce as forecasted and challenges that greater longevity brings (Gratton & Scott, Commission, 2010). Many European member states are far national economies already acknowledged the Commission, 2010). Many(2018) European member states arewill far by European Commission - Ageing Report 2018 national economies already acknowledged the opportunities 2017). Zacher et al. (2018) similarly add(Gratton thatopportunities continuous Commission, 2010). Many European member states are far from achieving this target. Shrinking workforce as forecasted national economies already acknowledged the opportunities and challenges that greater longevity brings & Scott, by European Commission (2018) Ageing Report 2018 will 2017). Zacher et al. (2018) similarly add that continuous from achieving this target. Shrinking workforce as forecasted and challenges that greater longevity brings (Gratton & Scott, from achieving this target. Shrinking workforce as forecasted lead to shortages in organizational workforce in specific and challenges that greater longevity brings (Gratton & rising Scott, from shrinking of births rates, ageing of the population and achieving this target. Shrinking workforce as forecasted by European Commission (2018) Ageing Report 2018 will and challenges that greater longevity brings (Gratton & Scott, 2017). Zacher et al. (2018) similarly add that continuous to shortages in organizational workforce in2018 specific shrinking of births rates, ageing of the population and rising lead by European (2018) -- Ageing will 2017). Zacher et and al. (2018) similarly addthe that continuous by European Commission (2018) Report 2018 will countries andCommission / or in specific sectors in the Report very near future 2017). Zacher et al. (2018) similarly add that continuous life expectancies retirement ages are main reasons by European (2018) - Ageing Ageing 2018 will lead to shortages in organizational workforce specific 2017). Zacher et and al. (2018) similarly addthe that continuous shrinking of births rates, ageing of the population and rising countries andCommission / or in specific sectors in the Report very in near future life expectancies retirement ages are main reasons lead to shortages in organizational workforce in specific shrinking of births rates, ageing of the population and rising (Zacher et al., 2018). According to the World Health shrinking of births rates, ageing of the population and rising lead to shortages in organizational workforce in specific causing the global population and workforce ageing. lead to shortages in organizational workforce in specific countries and / or in specific sectors in the very near future shrinking of births rates, ageing of the population and rising life expectancies and retirement ages are the main reasons et al., 2018). According to the very World Health causing the global population ages andare workforce ageing. (Zacher and //itor specific sectors in the near future life expectancies and retirement the main reasons countries and in specific sectors in the very near future Organization isin forecasted that to organizations in the life expectancies and ages are the main reasons Consequently researchers and practitioners around world countries countries andal., /itor or2018). in forecasted specific sectors inorganizations the very nearin future (Zacher et According the World Health life expectancies and retirement retirement ages areworkforce the mainthe reasons causing the global population and ageing. Organization is that the Consequently researchers and practitioners around the world (Zacher et al., 2018). According to the World Health causing the global population and workforce ageing. (Zacher et al., 2018). According to the World Health healthcare sector around the globe will have a shortage of 13 causing the global population and workforce ageing. are concerned about solving the problems related to the topic (Zacher etsector al., 2018). According the a World Health Organization it is forecasted causing the researchers globalsolving population and workforce ageing. Consequently and around world around the globethat willtoorganizations have shortagein of the 13 are concerned about thepractitioners problems related tothe the topic healthcare Organization it is forecasted that organizations in the Consequently researchers and practitioners around the world Consequently researchers and practitioners around the world Organization it is forecasted that organizations in the it around is forecasted that inof the healthcare sector the globe will organizations have aa shortage 13 Consequently andthepractitioners aroundtothe are concerned about solving problems related theworld topic Organization are concerned researchers about solving healthcare sector sector around around the the globe globe will will have have a shortage shortage of of 13 13 are about solving the the problems problems related related to to the the topic topic healthcare are concerned concerned about Copyright © 2019 IFAC solving the problems related to the topic2728healthcare sector around the globe will have a shortage of 13 2405-8963 © 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved. Copyright © 2019 IFAC 2728 Peer review under responsibility of International Federation of Automatic Control. Copyright © 2019 IFAC 2728 Copyright © 2019 IFAC 2728 10.1016/j.ifacol.2019.11.610 Copyright 2728 Copyright © © 2019 2019 IFAC IFAC 2728
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million workers by the year 2035, which means that the issues of ageing and finding a solution how to retain older workers should be discussed with high priority. As nowadays older individuals are living longer, are healthier and fitter than previous generations, advancement in technology such as growing automation (Acemoglu & Restrepo, 2017) and other ergonomic solutions (Bogataj et al., 2017a) are also boosting the productivity of older individuals. Berg et al. (2017) regarding the aforementioned problems argue that population ageing will have significant implications on several important fields, such as the labor market and the changing age structure of workforce within organizations. Dimovski and Colnar (2017) add that ageing of the population will also impact changes in the field of employment policies and housing (Bogataj et al., 2015, 2016). According to Peterson and Spiker (2005) the ageing global workforce was projected to be a dominant factor for business and organizations in the next two decades due to a growing shortage of knowledgeable and competent professionals in the global workforce pool. Already back in 2005 many key industries were experiencing problems as there were simply not enough technically qualified people to replace those that retired in their organizations (Peterson & Spiker, 2005; Hewitt, 2008). Berg et al. (2017) add that ageing is not only a pressing issue in terms of a gap in youngers workers and in terms of the need for reorganization of social programs focused on taking care of the elderly (i.e. long term care), it also massively reduces the functional capabilities of the workforce if we assume that younger workers on average are more productive than older workers. Due to increased longevity people are now more and more aware that is it extremely unlikely that they will have enough savings to normally retire at the age of 65 (Gratton & Scott, 2016). According to Börsch-Supan (2013) the solution is to add more labour into our ageing economies and that in order to be able to use to full potential the entire range of labour market policies should be used, including earlier labour market entry and later exit (retirement age), lower unemployment and higher female labour force participation. Froelich (2016) argues that for employees to remain competitive they will have to acknowledge to adapt to changes and to keep learning throughout their whole career. Workers will need to learn how to operate cyber-physical systems (Bogataj et al., 2017c), collaborate with robots (Battini et al., 2017) and operate smart production cells (Bogataj et al., 2017b, 2018). Benefits of this technologies can be evaluated with Net Present Value approach (Bogataj et al., 2017a, 2018), using MRP approach which development in last 50 years was explained by (Bogataj & Bogataj, 2018a). Organisations that will not embrace new technologies will need to develop early retirement occupational pension scheems that will increase their production cost (Bogataj et al., 2013). To put the concept of active ageing into workforce context, Zacher et al. (2018) define the three main characteristics that older workers try to maintain or aim to improve. First, their physical, mental and social well-being, second, their high levels of work engagement and performance, and third, their perceived experience of fair
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treatment and employment security. As such, active ageing should be perceived as an important goal for individuals, organizations, and society as a whole. Gratton and Scott (2017) forecast that due to increased longevity people that are currently in their mid-40s are expected to work into their early to mid-70s, and young people currently in their 20s will according to the current trend have to work in their late 70s or even into their 80s. In understanding the differences between different age groups it is important to acknowledge their future time perspective, which is defined by authors Froehlich et al. (2014) as the perception of individuals of how much time they have left in their future life, in terms of a workplace setting and their career. Lang and Carstensen (2002) highlight that this concept is correlated strongly and negatively with age. This further means that younger employees tend to focus more on learning, as they expect a longer period of when the learned knowledge or skill acquired will be beneficial for them. In comparison, people that are relatively close to their retirement find that this “payback” period is considerably shorter. In a nutshell this means that people close to the end of their working career are less motivated to invest a larger amount of resources, especially their time into learning activities (Froehlich, 2016). A suggestion by Froehlich (2016) is therefore that organizations should promote and make time for learning of their employees, as this can be particularly useful when dealing with an ageing workforce as in previous studies (i.e. Charness, 2008; Salthouse, 1996) researchers have already proven that ageing has negative effects on an individual’s ability of processing speed and working memory, which can expose the employee to a high amount of undesirable pressure and too high workload. Similarly, there is evidence in the literature that in the past the demand for older workers was negatively influenced by progressive developments of information and communication technology (hereinafter ICT) and innovative work practices (i.e. Aubert et al., 2006; Beckmann, 2007; Ronningen, 2007). This is further highlighted by the fact that ICT increases the skill gap. The vast majority of older workers completed their education in the more distant past in comparison with their younger colleagues, therefore they are experiencing a higher degree of competence loss due to the aforementioned advancements. To overcome this challenge, organizations need to focus on continuous training opportunities for older workers as an instrument to help them retain their working position and stay in the workforce for a longer period (Behaghel et al., 2014). Authors Behaghel et al. (2014) further suggest in their research that training has a positive impact on the employability of older workers however they argue that it only partially contributes in reducing the age bias that is associated with new technologies and innovative work practices. Moreover Behaghel et al. (2014) also suggest organizations to approach training of older workers with a bit of caution as they argue that when aiming to increase the employability of older workers, training cannot be the only answer as we live in a world that is increasingly expanding in terms of technological and organizational innovations, therefore older workers will also have to adapt in their understanding and knowledge about ICT and learn to
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collaborate with robots (Battini et al., 2017, Bogataj et al., 2017c, 2018). Similarly, organizations must also devote more time and resources to stimulate learning on all organizational levels, individual, team, organizational and interorganizational (Grah et al., 2016); in particular emphasizing helping older workers understand and adapt to new knowledge and new communication and organizational devices and implement this newly gained knowledge into practice to become truly learning organizations (Dimovski et al., 2005). The aim of this paper is to present a multiple decrement model of workforce transition and exit as this model allows measuring the quality of the organizational age management system. The objective of the paper is to present a more objective measuring tool that is based on actuarial – mathemiatical method. Furthermore, the objective of this paper is to present how to develop an actuarial model for determing the quality of the age management system of EU member states and how to evaluate the development of age management policies and other social policies for older workers in Slovenian regions. 2. THE MODEL 2.1 Multiple decrement model The basic multiple decrement models were already developed by Bogataj et al. (2015, 2016) and Rogelj and Bogataj (2018). For successful forecasting of different states (categories and functional capacities of workers), we will develop the multiple decrement model. The basic model enables to forecast the number of workers exiting labour force in each age cohort and derives the probabilities of transition at various ages on the organizational and national level, based on a demographic multiple decrement model (Deshmukh, 2012; Promislow, 2015). The model will enable long-term projections of available workforce in different states of productivity. The model will also enable an understanding of how different tools of age management influence the dynamics of available workforce in different productivity states. The increase in number of workers because of newly available age management tools has not been included in the model yet. The majority of industrial workforce who are over the age of 55 do not expect to retire until well after the historically determined retirement age. As industrial workers age, physical and cognitive changes occur. Several studies have already documented a decay of cognitive functions (Prakash et al, 2009), as well visual problems (Bucur et al., 2005) and physical (motor) capacities (Lindberg et al., 2009). All of the described physiological declines, also presented in figure 1, correlate to a decreased level of working performances in quality and quantity and also increase the variability of these performances in observed time windows. There is a threshold at which workers fall into the category at which are no longer able to perform their duties in their workplace. The dynamics of industrial workers functional capabilities is shown in figure 1. The workers may move among various states such as potential industrial employee, employeed trainee, employeed, fully productive, employed, partially productive,
unemployed, retired and dead. The used multiple decrement model, currently used in disability insurance will be extended as a tool for age management and forecasting the workforce exit. In multiple decrement models that have m different states for workers and retirees, there are m + 1 states for transition from one state to another (the second usually being less productive). Figure 1: Dynamics of functional capacities of industrial workers
We denote the initial state where worker is potential industrial employee as state 0 and decrement, which requires workplace/state of type j by the line of the graph from this child node to the state (node) j, j = 1, 2, … m. The model should describe the probabilities of transition from state 0 to state j∈H (where H is set of different types of workplaces/states) or, in general, from the child node to node j at various time points. All paths to j determine the dynamics of age management (state of type j) or different type of workforce exit (unemployed, retired, dead). In a multipledecrement setup, transitions between any two states, from i to j, i > j = 1, 2, … m, are not possible (directed graph). However, in a multi-state transition, we can also assume such transitions and an undirected graph, i.e., a set of objects (vertices and nodes) that are connected together such that all of the edges are bidirectional except to the last node (Gerber, 1997; Deshmukh, 2012). Senior workers can move among various states regarding their cognitive and physical functional capacities and willingness to work. Let us consider a worker aged x denoted by (x). We denote the future work period of the worker that she/he will spend in a current state of type i∈H by Ti(x). Thus x + Ti(x) will be the age when the worker exits out of his or her current state i and enters new state j, j∈H, which means a transit to a less productive category of type j or death. The future work period in the category of type i, Ti(x), is a random variable with probability distribution function: Gi (t) = Pr (Ti ≤ t), t ≥ 0
(1)
The function Gi(t) represents the probability that the worker will die or transfer to less productive state of type j within t years, for any fixed t. We assume that Gi(t), the probability distribution of Ti, is known. We also assume that Gi(t) is continuous and has probability density gi(t) = Gi‘(t). Data for Gi(t) should be available from national statistics. Thus, one can describe: gi (t) dt = Pr (t < T i < t + dt, j∈H)
(2)
where (2) describes the probability that the worker will transfer from state of type i in the infinitesimal time interval from t to t+dt. Therefore, the probability that a worker aged x
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in state i will transfer into a state of type j within t years is denoted by the symbol t qx (i, j). We have thus the known relationship: (3) t q x (i, j) = G(i, j:t) Similarly, one can write: t p x (i)
= 1 - G(i, j:t)
(4)
which denotes the probability that a worker aged x will remain in his or her current state at least t years. The graph starts at initial state i = PIE (potential industrial employee). We can observe all possible paths from PIE through some of the identified child nodes j∈H, which enable different exits from states as presented in figure 2 and figure 3. These include the possibility of exiting of workforce by employment, retirement and/or transition to the dead state. Figure 2: Transitions between different states (workplaces)
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The quality of age management is one of the components influencing the intensity of transition (Bogataj & Bogataj, 2018b). The details of the transition will be modelled as a directed graph. By observing all the possible paths from the initial state through transition types of states in different states (transition nodes in the graph), based on national demographic statistics, one can calculate the expected labour supply of different productivity and the age management tools needed for such transitions which will be subject of further research. The model will be further developed, previously based on the theoretical foundations published by Bogataj et al. (2015). 3. THE CASE STUDY FOR SLOVENIAN INDUSTRIAL WORKERS The transition matrix could be written based on demographic data and employment tables for different occupation groups for the year 2017, which were collected on the national level by the Slovenian Statistical Office (2017). The structure of male industrial workers aged 55 years old that are distinguished due to their different level of productivity is written with vector Sx as the sum of internal reallocations and net transitions of cohort:
Figure 3: Transitions between different states (workplaces)
Given the allocation of male industrial workers by type of for the studied cohort in the following year (when they are x+1 years old) we can calculate: Types of states: PIE – Potential Industrial Employee; ETR – Employed Trainee, EFP – Employed, Fully Productive, EPP – Employed, Partially Productive, PE – Partially Employed, UE – Unemployed, R – Retired, D – Dead
Forecasting future distribution of workers S according to the type of state based on current distribution of workers among different types of states and matrix of transitions among different types of states for workers x years old in multiple decrement model (i→j; i∈H, j∈H) will be described by transition equations:
(5)
This means that ageing of the population will decrease the availability of human resources as is seen from the example of male industrial workers. Therefore it is essential to emphasize the importance of understanding productivity of different groups of workers for organizations in different sectors and also at the national level in order to stay competitive in the long term. In trying to maintain or improve the availiability of workforce, the quality of age management is especially important as it encourages older workers to remain active for a longer period with measures that aim to improve i.e. occupational safety and health of an ageing worker. To stay competitive in the long term sustainable manufacturing workforce solutions are required. Furthermore in table 1 authors present the forecast regarding the availability of male industrial workers aged 55 in 2017 up to the studied year 2032 when they will be 70 years old.
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Table 1: Male industrial workers aged 55 in 2017 to aged 70 in 2032 Potential Employed, Employed, Employed Partially Industrial Fully Partially Unemployed Trainee Employed Employee Productive Productive 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032
7,983 7,184 6,466 5,819 5,237 4,713 4,242 3,818 3,436 3,092 2,783 2,505 2,254 2,029 1,826 1,643
42 80 72 65 58 52 47 42 38 34 31 28 25 23 20 18
920 854 827 791 749 704 657 611 565 521 478 438 401 366 333 303
335 303 274 251 231 213 196 180 165 151 137 125 114 104 94 85
42 174 260 315 346 361 364 358 346 331 312 293 273 253 233 215
3,107 3,212 3,317 3,415 3,500 3,573 3,629 3,670 3,695 3,704 3,699 3,680 3,648 3,606 3,554 3,493
Retired
Dead
3,107 3,573 4,009 4,418 4,800 5,157 5,490 5,800 6,090 6,359 6,608 6,840 7,054 7,252 7,435 7,603
0 155 309 461 612 761 909 1,055 1,200 1,343 1,485 1,626 1,765 1,902 2,039 2,174
Data source: Slovenian Statistical Office (SURS); own calculations 4. CONCLUSIONS The results are highly relevant and bring important potential impact due to the facts that: (1) Existing pension scheme is not sustainable in the long term. (2) Extension of working period is not well accepted by general public, even now high percentage of people in Slovenia retire before achieving full working period due to health problems. (3) Income tax is among highest in EU. (4) At the moment, organizational capacities regarding age management and investments in age management are very low. However, it is seen as possible solution to improve workers’ health and longevity. In this way workers will be not only be forced to work longer, but also be able and willing to, work longer. (5) Developed model allows better understanding of patterns of workforce exit and can be used by: (1) organizations in order to understand the workers’ demographics as well as the impact of age management policies and processes; (2) workers’ unions, e.g. within negotiating processes; (3) policy makers, when developing new policies (e.g. national taxation and retirement policies). In the long term, the results will also bring important contributions regarding assuring social equality, longlivity and healthier population and therefore affect the sustainability of public finances, in line with Europe 2020 strategy, as well as national policies related to age management (Vlada RS, 2018; Vlada RS, Ministrstvo za delo, družino, socialne zadeve in enake možnosti & Urad za makroekonomske analize in razvoj 2017). Any industrial organization that wants to be resilient and sustainable on the long-term, requires an appropriate number of fully functional industrial workers. The presented results are also crucial for industrial organizations to be able to plan their long term available productive workforce that will support sustainable mafucaturing workforce through implementing appropriate age management activities. On the other hand, the presented results can also be used by policy makers and worker unions to evaluate the efficiency and effectiveness of national retirement policies (Bogataj et al., 2013). REFERENCES 1.
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