Argumentos de los gobiernos españoles

Having appropriate informational and logistics structures govern the SC activities of e-grocery is a priority in the current marketplace (Punakivi and Saranen, 2001). However, their success depends on the availability of frameworks able to prioritize the main contributing factors and stakeholders prior to their implementation. In particular, the benefits for both the users and the companies providing the supporting services should be assessed from a quantitative point of view. In addition, e-grocery is generally recognised as a discontinuous innovation because it implies technological advances and patterns of behaviour completely different from choosing groceries from supermarket shelves, especially when it comes to fresh food (Hansen, 2005; Lim et al., 2009). Also, innovations like e-grocery, usually based on technological architectures made up of multiple modules carrying out different functions, bring strong interconnections among technology, business policies, and economic performance (Koellinger, 2008). Such mutual influences together with the novelty of the e-grocery paradigm add substantial

26 complexity to organisational systems that are already complex such as SCs (Choi et al., 2001). Thus, a methodological approach relying on tools to capture and deal with complexity is necessary to properly assess the practicality and effects of new products and services on business processes. To that end, the present work builds upon a well-established methodology for studying complex systems and a consolidated model for innovation diffusion to put forward a managerial approach to analyse the pattern of adoption of a mobile service for order, inventory, and delivery management. The impacts of this service on SC processes are also highlighted. From an academic point of view, this contribution stresses the need to go beyond the traditional perspective focused on final consumers and to consider how mobile information technologies may benefit the whole e-grocery SC, including B2B partners, thus stimulating its integration (Cassivi et al., 2005; Subba Rao et al., 2003; Yrjölä, 2001). Additionally, the work suggests that a structured ex-ante evaluation of the actual potential of new e-grocery services can be an important factor in surviving in today’s challenging and dynamic business context. Finally, the developed model stimulates the combination and adaptation in the area of SCM of literature-based SD models addressing the topic of innovation diffusion.

From a practitioners’ point of view, the proposed approach offers a roadmap to identify the key enabling factors of the diffusion of mobile e-grocery and to simulate their impact overtime. This can purposefully complement feasibility studies and marketing investigations when either introducing new services or upgrading existing ones. Also, it may support decision making about specific business policies. Moreover, such an assessment may facilitate the development process of telecommunication services in order to refine the choice of the enabling technologies before the prototype phase, with

27 significant savings in terms of investment costs. Additionally, the SC part of the developed SD model may help companies to anticipate the positive and negative effects on business processes of entering the e-grocery market. Finally, the flexibility of the SD methodology enables not only quantitative but also qualitative evaluations according to the availability of information.

Future research can extend the scope of the model to include additional players with different approaches to the use of the service and further factors affecting the expansion of mobile e-grocery. Also, the connection between this work and the concept of smart vehicles for freight distribution (Deflorio et al., 2010; Lee et al., 2011; Stefansson and Lumsden, 2009) might be explored.

In conclusion, the work presents a comprehensive decision-making approach to understand the factors that might influence the dynamics of growth of a mobile service supporting the e-grocery SC. The framework also suggests a methodology for studying the interconnections between the diffusion of e-grocery services and SC processes and can be accommodated to be applied to different services.

References

Al-Debei, M.M., Al-Lozi, E. and Fitzgerald, G. (2013), “Engineering innovative mobile data services Developing a model for value network analysis and design”, Business Process Management Journal, Vol. 19 No.2, pp.336-363.

Aldin, N., Brehmer, P-O. and Johansson, A. (2004), “Business development with electronic commerce: refinement and repositioning”, Business Process Management Journal, Vol. 10 No.1, pp.44-62.

28 An, L. and Ramachandran, B. (2005), “System Dynamics Model to Understand Demand Conditioning Dynamics in Supply Chains”, paper presented at the 23^rd International Conference of the System Dynamics Society, 17-21 July, Boston, MA.

Anderson, E.G. and Morrice, D.J. (2000), “A simulation game for service-oriented supply chain management”, Journal of Production and Operations Management, Vol. 9 No.1, pp.40-55.

Anderson Jr., E.G., Morrice, D.J. and Lundeen, G. (2005), “The “physics” of capacity and backlog management in service and custom manufacturing supply chains”, System Dynamics Review, Vol. 21 No.3, pp. 217-247.

Ashayeri, J. and Lemmes, L. (2006), “Economic value added of supply chain demand planning: a system dynamics simulation”, Robotics & Computers-Integrated Manufacturing, Vol. 22 No.5/6, pp.550-556.

Barnes, S.J. (2002), “The mobile commerce value chain: analysis and future developments”, International Journal of Information Management, Vol. 22 No.2, pp.91-108.

Bass, F.M. (1969), “A New Product Growth for Model Consumer Durables”, Management Science, Vol. 15 No.5, pp.215-227.

Ben Maalla, E.M. and Kunsch, P.L. (2008), “Simulation of micro-CHP diffusion by means of System Dynamics”, Energy Policy, Vol. 36 No.7, pp. 2308-2319.

Cagliano, A.C., De Marco, A., Rafele, C. and Volpe, S. (2011), “Using system dynamics in warehouse management: a fast-fashion case study”, Journal of Manufacturing Technology Management, Vol. 22 No.2, pp. 171-188.

29 Cassivi, L., Léger, P-M. and Hadaya, P. (2005), “Electronic commerce and supply chain integration: the case of the telecommunication equipment industry”, Business Process Management Journal, Vol. 11 No.5, pp.559-572.

Chen, J.V., Yen, D.C. and Chen, K. (2009), “The acceptance and diffusion of the innovative smart phone use: A case study of a delivery service company in logistics”, Information & Management, Vol. 46 No. 4, pp. 241-248.

Choi, T.Y., Dooley, K.J. and Rungtusanatham, M. (2001), “Supply networks and complex adaptive systems: control versus emergence”, Journal of Operations Management, Vol. 19 No.3, pp. 351-366.

Chu, W-L., Wu, F-S., Kao, K-S. and Yen, D.C. (2009), “Diffusion of mobile telephony:

An empirical study in Taiwan”, Telecommunications Policy, Vol. 33 No.9, pp. 506-520.

Corbett, J.J. (2001), “Is online grocery shopping increasing in strength?”, Journal of Food Distribution Research, Vol. 32 No. 1, pp. 37-40.

Cronrath, E-M. and Zock, A. (2007), “Forecasting the Diffusion of Innovations by Analogies: Examples of the Mobile Telecommunication Market”, paper presented at the 25^th International Conference of the System Dynamics Society, 29 July - 2 August, Boston, MA.

Croson, R. and Donohue, K. (2005), “Upstream versus downstream information and its impact on the bullwhip effect”, System Dynamics Review, Vol. 21 No.3, pp. 249-260.

Dahan, M. (2011), “Modeling the Diffusion of Innovations for Extended Reach to ICT and Mobile Technologies. A System Dynamics Approach”, paper presented at the 2011 IEEE Global Humanitarian Technology Conference, 30 October - 1 November, Seattle, WA.

30 Daim, T. and Suntharasaj, P. (2009), “Technology diffusion: forecasting with bibliometric analysis and Bass model”, Foresight, Vol. 11 No. 3, pp. 45-55.

De Koster, R.B.M. (2002), “Distribution structures for food home shopping”, International Journal of Physical Distribution & Logistics Management, Vol. 32 No. 5,

pp. 362-380.

Deflorio, F., Gonzales-Feliu, J., Perboli, G. and Tadei, R. (2012), “The Influence of Time Windows on the Costs of Urban Freight Distribution Services in City Logistics Applications”, European Journal of Transport and Infrastructure Research, Vol. 12 No.3, pp. 256-274.

Deflorio, F., Perboli, G. and Tadei, R. (2010), “Freight distribution performance indicators for service quality planning in large transportation networks”, Flexible Services and Manufacturing Journal, Vol. 22 No.1/2, pp. 36-60.

De Marco, A., Cagliano, A.C., Nervo, M.L. and Rafele, C. (2012), “Using System Dynamics to assess the impact of RFID technology on retail operations”, International Journal of Production Economics, Vol. 135 No.1, pp. 333-344.

Fisher, J.C. and Pry, R.H. (1971), “A simple substitution model of technological change”, Technology Forecasting and Social Change, Vol. 3 No.1, pp. 75-88.

Forrester, J.W. (1961), Industrial Dynamics, MIT Press, Cambridge, MA.

Georgiadis, P., Vlachos, D. and Iakovou, E. (2005), “A system dynamics modeling framework for the strategic supply chain management of food chains”, Journal of Food Engineering, Vol. 70 No.3, pp. 351–364.

Gonçalves, P., Hines, J. and Sterman, J. (2005), “The impact of endogenous demand on push-pull production systems”, System Dynamics Review, Vol. 21 No.3, pp. 187-216.

31 Hand, C., Dall’Olmo Riley, F., Harris, P., Singh, J. and Rettie, R. (2009), “Online grocery shopping: the influence of situational factors”, European Journal of Marketing, Vol. 43 No. 9/10, pp. 1205-1219.

Handel, O. (2014), “Demand Endogenization of Intermediate Products in Supply Chains through a System-Dynamics-based Modularization Concept”, paper presented at the 32^nd International Conference of the System Dynamics Society, 20-24 July, Delft, The Netherlands.

Hansen, T. (2005), “Consumer adoption of online grocery buying: a discriminant analysis”, International Journal of Retail & Distribution Management, Vol. 33 No. 2, pp. 101-121.

Hazen, B.T. and Byrd, T.A. (2012), “Toward creating competitive advantage with logistics information technology”, International Journal of Physical Distribution &

Logistics Management, Vol. 42 No. 1, pp. 8-35.

Huang, L. and Wang, Q. (2007), “The bullwhip effect in the closed loop supply chain”, paper presented at the 25^th International Conference of the System Dynamics Society, 29 July – 2 August, Boston, Massachusetts.

Kämäräinen, V. and Punakivi, M. (2004), “Unattended reception – a business opportunity?”, International Journal of Services Technology and Management, Vol. 5 No. 2, pp. 206-220.

Kauffman, R.J. and Techatassanasoontorn, A.A. (2005), “International Diffusion of Digital Mobile Technology: A Coupled-Hazard State-Based Approach”, Information Technology and Management, Vol. 6 No. 2/3, pp. 253-292.

32 Koellinger, P. (2008), “The relationship between technology, innovation, and firm performance – Empirical evidence from e-business in Europe”, Research Policy, Vol.

37 No.8, pp. 1317-1328.

Lee, L.H., Lee, C. and Bao, J. (2011), “The Impacts of an Electronic Marketplace with Multiple Independent Retailers for Smart Grocery Ordering Systems”, Wireless Personal Communications, Vol. 60 No.3, pp. 475-487.

Lim, H., Heilig, J.K., Ernst, S.C., Widdows, R. and Hooker, N.H. (2004), “Tracking the evolution of e-grocers: a quantitative assessment”, Journal of Food Distribution Research, Vol. 35 No. 2, pp. 66-82.

Lim, H., Widdows, R. and Hooker, N.H. (2009), “Web content analysis of e-grocery retailers: a longitudinal study”, International Journal of Retail & Distribution Management, Vol. 37 No. 10, pp. 839-851.

Liu, C. and Forsythe, S. (2011), “Examining drivers of online purchase intensity:

Moderating role of adoption duration in sustaining post-adoption online shopping”, Journal of Retailing and Consumer Services, Vol. 18 No.1, pp. 101-109.

Lu, H-P. and Su, P.Y-J. (2009), “Factors affecting purchase intention on mobile shopping web sites”, Internet Research, Vol. 19 No.4, pp. 442-458.

Lyneis, J.M. (1999), “System dynamics for business strategy: a phased approach”, System Dynamics Review, Vol. 15 No.1, pp. 37-70.

McIvor, R., Humphreys, P. and Huang, G. (2000), “Electronic commerce: re-engineering the buyer-supplier interface”, Business Process Management Journal, Vol.

6 No.2, pp.122-138.

Meade, N. and Islam, T. (2001), “Forecasting the diffusion of innovations: Implications for time series extrapolation”, in Armstrong, J.S. (Ed.), Principles of forecasting: A

33 handbook for researchers and practitioners, Kluwer Academic Publishers, Dordrecht,

The Netherlands, pp. 577-595.

Michalakelis, C., Dede, G., Varoutas, D. and Sphicopoulos, T. (2008a), “Impact of cross-national diffusion process in telecommunications demand forecasting”, Telecommunications Systems, Vol. 39 No. 1, pp. 51-60.

Michalakelis, C., Varoutas, D. and Sphicopoulos, T. (2008b), “Diffusion models of mobile telephony in Greece”, Telecommunications Policy, Vol. 32 No.3/4, pp. 234-245.

Minnich, D. and Maier, F.H. (2006), “Supply Chain Responsiveness and Efficiency-Complementing or Contradicting Each Other?”, paper presented at the 24^th International Conference of the System Dynamics Society, 23-27 July, Nijmegen, The Netherlands.

Morganosky, M.A. and Cude, B.J. (2000), “Consumer response to online grocery shopping”, International Journal of Retail & Distribution Management, Vol. 28 No.1, pp. 17-26.

Murtaza, M.B., Gupta, V. and Carroll, R.C. (2004), “E-marketplaces and the future of supply chain management: opportunities and challenges”, Business Process Management Journal, Vol. 10 No.3, pp. 325-335.

Nejad Amiri, A.A. and Kian, M.T. (2008), “Increasing Mobile Operator Revenue Out of VAS, A System Dynamics Approach”, paper presented at the 26^th International Conference of the System Dynamics Society, 20-24 July, Athens, Greece.

Panov, S.A. and Shiryaev, V.I. (2003), “Manufacturing supply chain adaptive management under changing demand conditions”, paper presented at the 21^st International Conference of the System Dynamics Society, 20-24 July, New York, NY.

34 Perboli, G., Pezzella, F. and Tadei, R. (2008), “EVE-OPT: a hybrid algorithm for the capability vehicle routing problem”, Mathematical Methods of Operations Research, Vol. 68 No.2, pp. 361-382.

Punakivi, M. and Saranen, J. (2001), “Identifying the success factors in e-grocery home delivery”, International Journal of Retail & Distribution Management, Vol. 29 No.4, pp. 156-163.

Raijas, A. (2002), “The consumer benefits and problems in the electronic grocery store”, Journal of Retailing and Consumer Services, Vol. 9 No.2, pp. 107-113.

Ramus, K. and Nielsen, N.A. (2005), “Online grocery retailing: what do consumers think?”, Internet Research, Vol. 15 No.3, pp. 335-352.

Salo, J. (2007), “Business relationships redesign with electronic commerce tools. An empirical investigation”, Business Process Management Journal, Vol. 13 No.4, pp.

488-502.

Shin, S., Lee, Y., Park, K., Choi, Y. and Kim, C. (2007), “Demand Forecasting on The Mobile Communication Service Market Using Diffusion Models and Growth Curve Models: A Case Study”, paper presented at the 6^th WSEAS International Conference on Applied Computer Science, 15-17 April, Hangzhou, China.

Stefansson, G. and Lumsden, K. (2009), “Performance issues of Smart Transportation Management systems”, International Journal of Productivity and Performance Management, Vol. 58 No.1, pp. 54-70.

Sterman, J.D. (2000), Business Dynamics: systems thinking and modeling for a complex world, McGraw – Hill.

35 Subba Rao, S., Metts, G. and Mora Monge, C. A. (2003), “Electronic commerce development in small and medium sized enterprises. A stage model and its implications”, Business Process Management Journal, Vol. 9 No.1, pp.11-32.

Tarofder, A.K., Marthandan, G., Mohan, A.V. and Tarofder, P. (2013), “Web technology in supply chain: an empirical investigation”, Business Process Management Journal, Vol. 19 No.3, pp. 431-458.

Thun, J-H., Gröβler, A. and Milling, P.M. (2000), “The Diffusion of Goods Considering Network Externalities: A System Dynamics-Based Approach”, paper presented at the 18^th International Conference of the System Dynamics Society, 6 – 10 August, Bergen, Norway.

Turk, T. and Trkman, P. (2012), “Bass model estimates for broadband diffusion in European countries”, Technological Forecasting & Social Change, Vol. 79 No.1, pp.

85-96.

Venkateswaran, J., Margabandu, K., Bijulal, D. and Hemachandra, N. (2011),

“Simulation-based Analysis of Service Levels in Stable Production-Inventory Systems”, paper presented at the 29^th International Conference of the System Dynamics Society, 24-28 July, Washington, DC.

Verhoef, P.C. and Langerak, F. (2001), “Possible determinants of consumers’ adoption of electronic grocery shopping in the Netherlands”, Journal of Retailing and Consumer Services, Vol. 8 No.5, pp. 275-285.

Vrechopoulos, A.P., Constantiou, I.D., Mylonopoulos, N. and Sideris, I. (2002),

“Critical Success Factors for Accelerating Mobile Commerce Diffusion in Europe”, paper presented at the 15^th Bled Electronic Commerce Conference. eReality:

Constructing the eEconomy, 17-19 June, Bled, Slovenia.

36 Wat, F.K.T., Ngai, E.W.T. and Cheng, T.C.E. (2005), “Potential risks to e-commerce development using exploratory factor analysis”, International Journal of Services Technology and Management, Vol. 6 No.1, pp. 55-71.

Wu, F-S. and Chu, W-L. (2010), “Diffusion models of mobile telephony”, Journal of Business Research, Vol. 63 No.5, pp. 497-501.

Yrjölä, H. (2001), “Physical distribution considerations for electronic grocery shopping”, International Journal of Physical Distribution & Logistics Management, Vol. 31 No.10, pp. 746-761.

Yücel, G. and van Daalen, C.E. (2009), “The Impact of Aggregation Assumptions and Social Network Structure on Diffusion Dynamics”, paper presented at the 27^th International Conference of the System Dynamics Society, 26 – 30 July, Albuquerque, New Mexico.

Zeithaml, V.A., Berry, L.L. and Parasuraman, A. (1993), “The Nature and Determinants of Customer Expectations of Service”, Journal of the Academy of Marketing Science, Vol. 21 No. 1, pp.1-12.

Zeng, E.Y., Yen, D.C, Hwang, H-G. and Huang, S-M. (2003), “Mobile commerce: the convergence of e-commerce and wireless technology”, International Journal of Services Technology and Management, Vol. 4 No.3, pp. 302-322.

Appendix

See on-line appendix

Figure 1. Architecture of the mobile service

Figure 2. Overview of the SD model

Consumer