The marketing firm and co‐creation: The case of co‐creation by LEGO

This article discusses the marketer and customer co‐creation process within the context of bilateral contingencies. Bilateral contingencies occur when the marketers' behavior is reinforced (and/or punished) by the customers' behavior, whereas the behavior of the customers is reinforced (and/or punished) by the marketers' actions. Using the example of the LEGO community, we discuss how the marketers in the organization can respond to behaviors resulting from co‐creational customer– customer exchanges. This paper fills the knowledge gap by presenting a behavior analysis framework (theory of the marketing firm) for the empirical measurement of the co‐creation process.The marketing firm and co‐creation: The case of co‐creation by LEGOacceptedVersio

The effectiveness of crowdsourcing in knowledge-based industries: the moderating role of transformational leadership and organisational learning

[EN] Crowdsourcing provides an opportunity for SMEs to exploit collective knowledge that is located outside the organisation. Crowdsourcing allows organisations to keep pace with a fast-changing environment by solving business problems, supporting R&D activities, and fostering innovation cheaply, flexibly, and dynamically. Nevertheless, managing crowdsourcing is difficult, and positive outcomes are not guaranteed. Drawing on the Resource-based View, we study transformational leadership and organisational learning capability as complementary assets to help SMEs deploy crowdsourcing. An empirical study of Spanish telecommunications and biotechnology companies confirmed the moderating effect of organisational learning on the relationship between crowdsourcing and organisational performance.Devece Carañana, CA.; Palacios Marqués, D.; Ribeiro-Navarrete, B. (2019). The effectiveness of crowdsourcing in knowledge-based industries: the moderating role of transformational leadership and organisational learning. Economic Research-Ekonomska Istra ivanja. 32(1):335-351. https://doi.org/10.1080/1331677X.2018.1547204S335351321Amitay, M., Popper, M., & Lipshitz, R. (2005). Leadership styles and organizational learning in community clinics. The Learning Organization, 12(1), 57-70. doi:10.1108/09696470510574269Atapattu, M., & Ranawake, G. (2017). Transformational and Transactional Leadership Behaviours and their Effect on Knowledge Workers’ Propensity for Knowledge Management Processes. Journal of Information & Knowledge Management, 16(03), 1750026. doi:10.1142/s0219649217500265Aragón-Correa, J. A., García-Morales, V. J., & Cordón-Pozo, E. (2007). Leadership and organizational learning’s role on innovation and performance: Lessons from Spain. Industrial Marketing Management, 36(3), 349-359. doi:10.1016/j.indmarman.2005.09.006Bal, A. S., Weidner, K., Hanna, R., & Mills, A. J. (2017). Crowdsourcing and brand control. Business Horizons, 60(2), 219-228. doi:10.1016/j.bushor.2016.11.006Barney, J. (1991). Firm Resources and Sustained Competitive Advantage. Journal of Management, 17(1), 99-120. doi:10.1177/014920639101700108Colli, A. (2011). Contextualizing Performances of Family Firms. Family Business Review, 25(3), 243-257. doi:10.1177/0894486511426872Bhatti, W. A., Larimo, J., & Carrasco, I. (2016). Strategy’s effect on knowledge sharing in host country networks. Journal of Business Research, 69(11), 4769-4774. doi:10.1016/j.jbusres.2016.04.028Bruque-Cámara, S., Vargas-Sánchez, A., & Hernández-Ortiz, M. J. (2004). Organizational determinants of IT adoption in the pharmaceutical distribution sector. European Journal of Information Systems, 13(2), 133-146. doi:10.1057/palgrave.ejis.3000490Cáceres, R., Guzmán, J., & Rekowski, M. (2011). Firms as source of variety in innovation: influence of size and sector. International Entrepreneurship and Management Journal, 7(3), 357-372. doi:10.1007/s11365-011-0198-8Chi, H.-K., Lan, C.-H., & Dorjgotov, B. (2012). The Moderating Effect of Transformational Leadership on Knowledge Management and Organizational Effectiveness. Social Behavior and Personality: an international journal, 40(6), 1015-1023. doi:10.2224/sbp.2012.40.6.1015Chiva, R., & Alegre, J. (2005). Organizational Learning and Organizational Knowledge. Management Learning, 36(1), 49-68. doi:10.1177/1350507605049906Chiva, R., Alegre, J., & Lapiedra, R. (2007). Measuring organisational learning capability among the workforce. International Journal of Manpower, 28(3/4), 224-242. doi:10.1108/01437720710755227Coelho, D. A., Nunes, F., & Vieira, F. L. (2016). The impact of crowdsourcing in product development: an exploratory study of Quirky based on the perspective of participants. International Journal of Design Creativity and Innovation, 6(1-2), 114-128. doi:10.1080/21650349.2016.1216331Conant, J. S., Mokwa, M. P., & Varadarajan, P. R. (1990). Strategic types, distinctive marketing competencies and organizational performance: A multiple measures-based study. Strategic Management Journal, 11(5), 365-383. doi:10.1002/smj.4250110504Devece, C., Palacios, D., & Martinez-Simarro, D. (2016). Effect of information management capability on organizational performance. Service Business, 11(3), 563-580. doi:10.1007/s11628-016-0320-7Dimitrova, S., & Scarso, E. (2017). The impact of crowdsourcing on the evolution of knowledge management: Insights from a case study. Knowledge and Process Management, 24(4), 287-295. doi:10.1002/kpm.1552Elkins, T., & Keller, R. T. (2003). Leadership in research and development organizations: A literature review and conceptual framework. The Leadership Quarterly, 14(4-5), 587-606. doi:10.1016/s1048-9843(03)00053-5Estellés-Arolas, E., & González-Ladrón-de-Guevara, F. (2012). Towards an integrated crowdsourcing definition. Journal of Information Science, 38(2), 189-200. doi:10.1177/0165551512437638Flostrand, A. (2017). Finding the future: Crowdsourcing versus the Delphi technique. Business Horizons, 60(2), 229-236. doi:10.1016/j.bushor.2016.11.007García-Morales, V. J., Lloréns-Montes, F. J., & Verdú-Jover, A. J. (2008). The Effects of Transformational Leadership on Organizational Performance through Knowledge and Innovation*. British Journal of Management, 19(4), 299-319. doi:10.1111/j.1467-8551.2007.00547.xGrant, R. M. (1991). The Resource-Based Theory of Competitive Advantage: Implications for Strategy Formulation. California Management Review, 33(3), 114-135. doi:10.2307/41166664King, W. R. (Ed.). (2009). Knowledge Management and Organizational Learning. Annals of Information Systems. doi:10.1007/978-1-4419-0011-1Lang, M., Bharadwaj, N., & Di Benedetto, C. A. (2016). How crowdsourcing improves prediction of market-oriented outcomes. Journal of Business Research, 69(10), 4168-4176. doi:10.1016/j.jbusres.2016.03.020Lee, J., & Seo, D. (2016). Crowdsourcing not all sourced by the crowd: An observation on the behavior of Wikipedia participants. Technovation, 55-56, 14-21. doi:10.1016/j.technovation.2016.05.002Leimeister, J. M., Huber, M., Bretschneider, U., & Krcmar, H. (2009). Leveraging Crowdsourcing: Activation-Supporting Components for IT-Based Ideas Competition. Journal of Management Information Systems, 26(1), 197-224. doi:10.2753/mis0742-1222260108Liu, S., Xia, F., Zhang, J., & Wang, L. (2016). How crowdsourcing risks affect performance: an exploratory model. Management Decision, 54(9), 2235-2255. doi:10.1108/md-12-2015-0604Marjanovic, S., Fry, C., & Chataway, J. (2012). Crowdsourcing based business models: In search of evidence for innovation 2.0. Science and Public Policy, 39(3), 318-332. doi:10.1093/scipol/scs009McEvily, S. K., & Chakravarthy, B. (2002). The persistence of knowledge-based advantage: an empirical test for product performance and technological knowledge. Strategic Management Journal, 23(4), 285-305. doi:10.1002/smj.223Melville, Kraemer, & Gurbaxani. (2004). Review: Information Technology and Organizational Performance: An Integrative Model of IT Business Value. MIS Quarterly, 28(2), 283. doi:10.2307/25148636Naqshbandi, M. M., & Tabche, I. (2018). The interplay of leadership, absorptive capacity, and organizational learning culture in open innovation: Testing a moderated mediation model. Technological Forecasting and Social Change, 133, 156-167. doi:10.1016/j.techfore.2018.03.017Assis Neto, F. R., & Santos, C. A. S. (2018). Understanding crowdsourcing projects: A systematic review of tendencies, workflow, and quality management. Information Processing & Management, 54(4), 490-506. doi:10.1016/j.ipm.2018.03.006Nonaka, I., & Konno, N. (1998). The Concept of «Ba»: Building a Foundation for Knowledge Creation. California Management Review, 40(3), 40-54. doi:10.2307/41165942Noruzy, A., Dalfard, V. M., Azhdari, B., Nazari-Shirkouhi, S., & Rezazadeh, A. (2012). Relations between transformational leadership, organizational learning, knowledge management, organizational innovation, and organizational performance: an empirical investigation of manufacturing firms. The International Journal of Advanced Manufacturing Technology, 64(5-8), 1073-1085. doi:10.1007/s00170-012-4038-yPalacios‐Marqués, D., Peris‐Ortiz, M., & Merigó, J. M. (2013). The effect of knowledge transfer on firm performance. Management Decision, 51(5), 973-985. doi:10.1108/md-08-2012-0562Palacios, M., Martinez-Corral, A., Nisar, A., & Grijalvo, M. (2016). Crowdsourcing and organizational forms: Emerging trends and research implications. Journal of Business Research, 69(5), 1834-1839. doi:10.1016/j.jbusres.2015.10.065Peris-Ortiz, M., Devece-Carañana, C. A., & Navarro-Garcia, A. (2018). Organizational learning capability and open innovation. Management Decision, 56(6), 1217-1231. doi:10.1108/md-02-2017-0173Piezunka, H., & Dahlander, L. (2015). Distant Search, Narrow Attention: How Crowding Alters Organizations’ Filtering of Suggestions in Crowdsourcing. Academy of Management Journal, 58(3), 856-880. doi:10.5465/amj.2012.0458Podsakoff, P. M., MacKenzie, S. B., Lee, J.-Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879-903. doi:10.1037/0021-9010.88.5.879Prpić, J., Shukla, P. P., Kietzmann, J. H., & McCarthy, I. P. (2015). How to work a crowd: Developing crowd capital through crowdsourcing. Business Horizons, 58(1), 77-85. doi:10.1016/j.bushor.2014.09.005Qin, S., Van Der Velde, D., Chatzakis, E., McStea, T., & Smith, N. (2016). Exploring barriers and opportunities in adopting crowdsourcing based new product development in manufacturing SMEs. Chinese Journal of Mechanical Engineering, 29(6), 1052-1066. doi:10.3901/cjme.2016.0808.089Rai, Patnayakuni, & Seth. (2006). Firm Performance Impacts of Digitally Enabled Supply Chain Integration Capabilities. MIS Quarterly, 30(2), 225. doi:10.2307/25148729RAVICHANDRAN, T., LERTWONGSATIEN, C., & LERTWONGSATIEN, C. (2005). Effect of Information Systems Resources and Capabilities on Firm Performance: A Resource-Based Perspective. Journal of Management Information Systems, 21(4), 237-276. doi:10.1080/07421222.2005.11045820Ray, G., Barney, J. B., & Muhanna, W. A. (2003). Capabilities, business processes, and competitive advantage: choosing the dependent variable in empirical tests of the resource-based view. Strategic Management Journal, 25(1), 23-37. doi:10.1002/smj.366Schlagwein, D., & Bjorn-Andersen, N. (2014). Organizational Learning with Crowdsourcing: The Revelatory Case of LEGO. Journal of the Association for Information Systems, 15(11), 754-778. doi:10.17705/1jais.00380Schmallegger, D., & Carson, D. (2008). Blogs in tourism: Changing approaches to information exchange. Journal of Vacation Marketing, 14(2), 99-110. doi:10.1177/1356766707087519Stanko, M. A., Molina-Castillo, F.-J., & Harmancioglu, N. (2014). It Won’t Fit! For Innovative Products, Sometimes That’s for the Best. Journal of Product Innovation Management, 32(1), 122-137. doi:10.1111/jpim.12238STOCK, R. M., & SCHNARR, N. L. (2016). EXPLORING THE PRODUCT INNOVATION OUTCOMES OF CORPORATE CULTURE AND EXECUTIVE LEADERSHIP. International Journal of Innovation Management, 20(01), 1650009. doi:10.1142/s1363919616500092Templeton, G. F., Lewis, B. R., & Snyder, C. A. (2002). Development of a Measure for the Organizational Learning Construct. Journal of Management Information Systems, 19(2), 175-218. doi:10.1080/07421222.2002.11045727Tohidi, H., & Jabbari, M. M. (2012). Measuring organizational learning capability. Procedia - Social and Behavioral Sciences, 31, 428-432. doi:10.1016/j.sbspro.2011.12.079Vukovic, M. (2009). Crowdsourcing for Enterprises. 2009 Congress on Services - I. doi:10.1109/services-i.2009.56Wade, & Hulland. (2004). Review: The Resource-Based View and Information Systems Research: Review, Extension, and Suggestions for Future Research. MIS Quarterly, 28(1), 107. doi:10.2307/25148626Wu, I.-L., & Chen, J.-L. (2014). Knowledge management driven firm performance: the roles of business process capabilities and organizational learning. Journal of Knowledge Management, 18(6), 1141-1164. doi:10.1108/jkm-05-2014-0192Xie, X., Wang, L., & Zeng, S. (2018). Inter-organizational knowledge acquisition and firms’ radical innovation: A moderated mediation analysis. Journal of Business Research, 90, 295-306. doi:10.1016/j.jbusres.2018.04.038Ye, H. (Jonathan), & Kankanhalli, A. (2015). Investigating the antecedents of organizational task crowdsourcing. Information & Management, 52(1), 98-110. doi:10.1016/j.im.2014.10.007Zollo, M., & Winter, S. G. (2002). Deliberate Learning and the Evolution of Dynamic Capabilities. Organization Science, 13(3), 339-351. doi:10.1287/orsc.13.3.339.278

Prospects for seascape repair: Three case studies from eastern Australia

Three case studies spanning tropical, subtropical and temperate environments highlight the minimum potential benefits of investing in repair of coastal seascapes. Fisheries, a market benefit indicator readily understood by a range of stakeholders from policymakers to community advocates, were used as a surrogate for ecosystem services generated through seascape habitat restoration. For each case study, while recognising that biological information will always remain imperfect, the prospects for seascape repair are compelling

When grassroots innovation movements encounter mainstream institutions: implications for models of inclusive innovation

Grassroots innovation movements (GIMs) can be regarded as initiators or advocates of alternative pathways of innovation. Sometimes these movements engage with more established science, technology and innovation (STI) institutions and development agencies in pursuit of their goals. In this paper, we argue that an important aspect to encounters between GIMs and mainstream STI institutions is the negotiation of different framings of grassroots innovation and development of policy models for inclusive innovation. These encounters can result in two different modes of engagement by GIMs; what we call insertion and mobilization. We illustrate and discuss these interrelated notions of framings and modes of engagement by drawing on three case studies of GIMs: the Social Technologies Network in Brazil, and the Honey Bee Network and People's Science Movements in India. The cases highlight that inclusion in the context of GIMs is not an unproblematic, smooth endeavour, and involves diverse interpretations and framings, which shape what and who gets included or excluded. Within the context of increasing policy interest, the analysis of encounters between GIMs and STI institutions can offer important lessons for the design of models of inclusive innovation and development

Co-creation experiences: The next practice in value creation

Consumers today have more choices of products and services than ever before, but they seem dissatisfied. Firms invest in greater product variety but are less able to differentiate themselves. Growth and value creation have become the dominant themes for managers. In this paper, we explain this paradox. The meaning of value and the process of value creation are rapidly shifting from a product- and firm-centric view to personalized consumer experiences. Informed, networked, empowered, and active consumers are increasingly co-creating value with the firm. The interaction between the firm and the consumer is becoming the locus of value creation and value extraction. As value shifts to experiences, the market is becoming a forum for conversation and interactions between consumers, consumer communities, and firms. It is this dialogue, access, transparency, and understanding of risk-benefits that is central to the next practice in value creation.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/35225/1/20015_ftp.pd

Real Estate Investment Trusts (REITS) : A new business model in the FTSE100

CC-BY-NC-NDThis paper is about the Real Estate Investment Trust (REIT) business model. REITs benefit from tax concessions and Fair Value Accounting (FVA) practices. REITs distributing over 90 percent of profits can obtain tax concessions for their shareholders. This encourages profit distribution at the expense of accumulating retained earnings in shareholder equity. The financial viability of REITs depends upon FVA because this records holding gains when property values are increased. These holding gains can be employed to generate additional financial leverage. However, REITs are exposed to property market volatility and this can quickly undermine solvency, credit ratings and financial stability.Peer reviewedFinal Accepted Versio

Collaborative research and development (R&D) for climate technology transfer and uptake in developing countries: Towards a needs driven approach

While international cooperation to facilitate the transfer and uptake of climate technologies in developing countries is an ongoing part of climate policy conversations, international collaborative R&D has received comparatively little attention. Collaborative R&D, however, could be a potentially important contributor to facilitating the transfer and uptake of climate technologies in developing countries. But the complexities of international collaborative R&D options and their distributional consequences have been given little attention to date. This paper develops a systematic approach to informing future empirical research and policy analysis on this topic. Building on insights from relevant literature and analysis of empirical data based on a sample of existing international climate technology R&D initiatives, three contributions are made. First, the paper analyses the coverage of existing collaborative R&D efforts in relation to climate technologies, highlighting some important concerns, such as a lack of coverage of lower-income countries or adaptation technologies. Second, it provides a starting point for further systematic research and policy thinking via the development of a taxonomic approach for analysing collaborative designs. Finally, it matches characteristics of R&D collaborations against developing countries’ climate technology needs to provide policymakers with guidance on how to Configure R&D collaborations to meet these needs

Co-creation: Moving towards a framework for creating innovation in the triple helix

The objective of the paper is to demonstrate how the theoretical ideas of Service-Dominant Logic (S-D logic) can usefully be applied to innovation through collaboration between university, industry and government. The debate around S-D logic has stimulated much discussion around three areas that are particularly pertinent in considering the co-creation of knowledge within the Triple Helix. The first area relates to understanding the nature of the resources provided by all the parties involved and the process through which they are integrated. The second area relates to interaction between the parties involved. The third and most complex area relates to how value is perceived by the different parties. This discussion leads to a proposed model of the co-creation process and four suggested research agendas: Research Agenda One, relating to the resources supplied by the parties and their integration; Research Agenda Two, concerning the interaction practices that enhance co-creation; Research Agenda Three, exploring what value propositions will motivate the different parties to co-create; and Research Agenda Four, considering how co-creation modifies the resources of the parties involved. A model of the co-creation process that encompasses these four research agendas and provides a conceptual framework to analyse Triple Helix initiatives is proposed. Some practical implications are then discussed, relating to the challenges for researchers in identifying who to co-create with and understanding what value propositions will motivate potential partners

Expanding fish productivity in Tasmanian saltmarsh wetlands through tidal re-connection and habitat repair

Fish use of coastal saltmarsh wetlands has been documented for many parts of Australia with the notable exception of Tasmania. An initial investigation to examine the diversity, density and patterns of fish use in the Circular Head coast saltmarshes of north-west Tasmania was undertaken. To aid decision making in repair strategies, the effect of saltmarsh condition on fish assemblages was studied using paired sites of predominantly unaltered and altered saltmarshes where levees were present. In all, 851 fish from 11 species were caught in 37 of the 48 pop nets. Three species, Aldrichetta forsteri, Arripis truttaceus and Rhombosolea tapirina, are important to commercial and recreational fisheries and contributed ,20% of the total catch numbers. The mean density of .72 fish per 100 m2 is the highest yet reported from Australian studies and indicates that Tasmanian saltmarshes provide higher value habitat for fish compared with elsewhere in Australia, likely due to more frequent and prolonged flooding, and the lack of adjacent mangroves. There was no significant difference in fish assemblages between unaltered and altered marshes. The results suggest that restoring basic saltmarsh structure through tidal reconnection will deliver substantial benefits for fish productivity through habitat expansion