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The effect of social network structures at the business/IT interface on IT application change effectiveness

  • Research Article
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Journal of Information Technology

Abstract

The challenge of managing the relationship between a firm’s business and IT in order to derive business value from IT is an important topic on researchers’ and practitioners’ agendas. The focus of most related research and management actions has been on the top management or project management levels. However, conflicts frequently arise within the line organization when applications are extended, enhanced, maintained, or otherwise changed operationally outside software development projects. This study focuses on the impact of relationships at the application-change level and strives to identify and explain favorable social structures for effective business/IT dialog at the operational level. We collected data in seven comprehensive case studies, including 88 interviews and corresponding surveys, and applied social network analysis to show that three social structures at the implementation level influence the degree to which IT applications are maintained and enhanced in line with business requirements: (1) interface actors connecting business and IT, (2) the relationships between interface actors and the corresponding unit, and (3) the relationships between interface actors and other employees in their unit. In three cases, less favorable structures are revealed that correspond to low application change effectiveness and software applications that do not meet business requirements. The other cases benefit from favorable social structures and thus enhance fulfillment of business requirements and result in higher IT business value. This paper contributes to IS research by helping to explain why companies may not provide favorable IT services despite favorable relationships at the top management level and successful application development projects.

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Notes

  1. For example, the integration of complex new products into a sales application of an insurance company, which is necessary to bring the product to the market and might easily require several developer weeks.

  2. One might argue that newly hired colleagues often start their career in change and incident management. However, while this might be a common practice in software firms, we did not see a substantial portion of newly hired personnel in these functions in the cases we studied, which were non-software firms focusing on general businesses, for example, banking, insurance. Even colleagues hired into these departments stayed there for several years, while the largest number of actors had been with the firm for multiple years.

  3. In terms of the ITIL nomenclature, we thereby exclude ‘service design’ and ‘service strategy’ (Cabinet-Office, 2011) since these concern strategic decisions, which are not in the focus of our research.

  4. Such as: Do you agree to the following statement ‘He or she is an important consultant to me on work-related issues.’ (Scale: 1=fully disagree, 7=fully agree) (See Appendix E for all items and descriptive statistics).

  5. In two cases, we had to add one key interface actor because he missed that threshold despite the interviewees describing him or her as a very central person.

  6. Typically, one would accept to identify interface actors by using betweenness centrality; however, here two reasons did not allow to use this measure: first, we searched for a position between two distinct groups and would have needed to develop a complex measure based on Everett and Borgatti’s (1999) group betweenness centrality. Second, we witnessed several situations in which even such an adapted measure would not yield the correct results because it would not identify interface actors working in a team with other interface actors from their own unit who interact with similar people in the other unit. This type of interface actor was very common in our cases.

  7. Due to the use of two networks in our analysis, an actor not interacting frequently (network 1) with more than n/2 actors of the other unit, that is, a non-interface actor, might exhibit strong connections (network 2) to an interface actor of the other unit. These connections are ignored in the calculation of S1, which focuses on connections between two interface actors only. However, our measure ensures comparability across cases. If we had also factored in relationships to non-interface actors, cases with a higher number of involved (non-interface) actors would have had lower scores, since the denominator would have involved all actors in the other unit. Yet, by design, the interface actor would have been connected only to some of them. Thus in cases with a lower number of (non-interface) actors in the other unit, the portion of non-interface actors with whom an interface actor is strongly connected may be more favorable than in larger cases.

  8. For this step of standardization and to keep cases comparable, we used only those actors who were part of the connected core network within a unit. Larger cases contain more actors. However, since we were unable to gather SNA data from all of them and since the portion of within-unit actors who did not answer the SNA questionnaire was greater in these cases (because the number of actors in one’s own unit that an actor could name was limited to five) and since, finally, the capacity of interface actors building strong ties to other actors is limited (Granovetter, 1973), there is a higher risk of within-unit actors becoming isolates in the relationship network in larger cases. This risk is structurally related to our data collection approach and not to deficient structures in the network. Hence, we limit the effect of these isolates by excluding them from the standardization calculation. Since we gathered data from all key actors, we can assume that these isolates are not only peripheral in the network data but also in their unit.

  9. An exception is the discussion of complementary knowledge in outsourced software development projects in Kim et al. (2010).

  10. Particularly, we applied two rounds of data gathering with the SNA questionnaire: The first was done based on the persons highlighted in the initial interview with the management, while the second round addressed persons that were identified in the interviews and mentioned in the SNA questionnaire. Actors who in the first round turned out to be central were also interviewed in a second round.

  11. As already argued in the introductory section, this might not hold true for software firms; there we typically a less clear separation of ‘IT’ and ‘business’ since the business is about producing IT.

References

  • Adler, P.S. and Kwon, S.-W. (2002). Social Capital: Prospects for a new concept, Academy of Management Review 27 (1): 17–40.

    Google Scholar 

  • Ancona, D. and Caldwell, D. (1992). Bridging the Boundary: External activity and performance of organizational teams, Administrative Science Quarterly 37 (4): 634–665.

    Article  Google Scholar 

  • Auerbach, C.F. and Silverstein, L.B. (2003). Qualitative Data: An introduction to coding and analyzing, New York, London: New York University Press.

    Google Scholar 

  • Azarian, R. (2010). Social Ties: Elements of a substantive conceptualization, Acta Sociologica 53 (4): 323–338.

    Article  Google Scholar 

  • Behrens, S. (2009). Shadow Systems: The good, the bad and the ugly, Communications of the ACM 52 (2): 124–129.

    Article  Google Scholar 

  • Brennan, O. (2008). Client and IT Engagement in Software Development: A disconnect of mindsets, in Australian Conference on Information Systems (ACIS).

  • Burt, R.S. (1982). Toward a Structural Theory of Action: Network models of social structure, perception, and action, New York: Academic Press.

    Book  Google Scholar 

  • Cabinet-Office (2011). ITIL Lifecycle Publication Suite, Norwich: The Stationery Office.

  • Carlile, P.R. (2002). A Pragmatic View of Knowledge and Boundaries: Boundary objects in new product development, Organization Science 13 (4): 442–455.

    Article  Google Scholar 

  • Chan, Y.E. (2002). Why Haven‘t We Mastered Alignment?: The importance of the informal organization structure, MIS Quarterly Executive 1 (2): 97–112.

    Google Scholar 

  • Chan, Y.E. and Reich, B.H. (2007). IT Alignment: What have we learned? Journal of Information Technology 22 (4): 297–315.

    Article  Google Scholar 

  • Chi, L. and Deng, X. (2011). Knowledge Transfer in Information Systems Support Community: Network effects of bridging and reaching, in International Conference on Information Systems (ICIS) (Shanghai).

  • Chua, C.E.H., Lim, W.-K., Soh, C. and Sia, S.K. (2012). Enacting Clan Control in Complex IT Projects: A social capital perspective, MIS Quarterly 36 (2): 577–600.

    Google Scholar 

  • Corbridge, C., Rugg, G., Major, N.P., Shadbolt, N.R. and Burton, A.M. (1994). Laddering: Technique and Tool use in Knowledge Aquisition, Knowledge Aquisition 6 (3): 315–341.

    Article  Google Scholar 

  • Cross, R., Parker, A., Prusak, L. and Borgatti, S.P. (2001). Knowing What We Know: Supporting knowledge creation and sharing in social networks, Organizational Dynamics 30 (2): 100–120.

    Article  Google Scholar 

  • Day, J. (2007). Strangers on the Train: The relationship of the IT department with the rest of the business, Information Technology & People 20 (1): 6–31.

    Article  Google Scholar 

  • Dhaliwal, J., Onita, C.G., Poston, R. and Zhang, X.P. (2011). Alignment within the Software Development unit: Assessing structural and relational dimensions between developers and testers, Journal of Strategic Information Systems 20 (4): 323–342.

    Article  Google Scholar 

  • Dubé, L. and Paré, G. (2003). Rigor in Information Systems Positivist Case Research: Current practices, trends, and recommendations, MIS Quarterly 27 (4): 597–635.

    Google Scholar 

  • Everett, M.G. and Borgatti, S.P. (1999). The Centrality of Groups and Classes, Journal of Mathematical Sociology 23 (3): 181–201.

    Article  Google Scholar 

  • Faraj, S. and Sproull, L. (2000). Coordinating Expertise in Software Development Teams, Management Science 46 (12): 1554–1568.

    Article  Google Scholar 

  • Feeny, D.F. and Willcocks, L.P. (1998). Core IS Capabilities for Exploiting Information Technology, Sloan Management Review 39 (3): 9–21.

    Google Scholar 

  • Fischer, C.S. (1982). To Dwell among Friends: Personal networks in town and city, Chicago: Chicago University Press.

    Google Scholar 

  • Friedman, R.A. and Podolny, J. (1992). Differentiation of Boundary Spanning Roles: Labor negotiations and implications for role conflict, Administrative Science Quarterly 37 (1): 28–47.

    Article  Google Scholar 

  • Gasson, S. (2006). A Genealogical Study of Boundary-spanning IS Design, European Journal of Information Systems 15 (1): 26–41.

    Article  Google Scholar 

  • Goh, J.C.-L., Pan, S.L. and Zuo, M. (2013). Developing the Agile IS Development Practices in Large-scale IT Projects: The trust-mediated organizational controls and IT project team capabilities perspectives, Journal of the Association for Information Systems 14 (12).

  • Granovetter, M.S. (1973). The Strength of Weak Ties, American Journal of Sociology 78 (6): 1360–1380.

    Article  Google Scholar 

  • Granovetter, M.S. (1982). The Strength of Weak Ties: A network theory revisited, in P.V. Marsden and N. Lin (eds.) Social Structure and Network Analysis, Beverly Hills: Sage Publications, pp. 105–130.

    Google Scholar 

  • Holland, D. and Skarke, G. (2008). Business & IT Alignment: Then & now, a striking improvement, Strategic Finance 89 (10): 43–49.

    Google Scholar 

  • Jetu, F.T. and Riedl, R. (2012). Determinants of Information Systems and Information Technology Project Team Success: A literature review and a conceptual model, Communications of the AIS 30 (1):Article 27.

    Google Scholar 

  • Johnson, A. and Lederer, A. (2005). The Effect of Communication Frequency and Channel Richness on the Convergence between Chief Executive and Chief Information Officers, Journal of Management Information Systems 22 (2): 227–252.

    Google Scholar 

  • Kearns, G.S. and Sabherwal, R. (2007). Strategic Alignment between Business and Information Technology: A knowledge-based view of behaviors, outcome, and consequences, Journal of Management Information Systems 23 (3): 129–162.

    Article  Google Scholar 

  • Kim, K.K., Shin, H.K. and Lee, M.H. (2010). The Influence of Partner Knowledge Complementarities on the Effectiveness of IT Outsourcing, Journal of Organizational Computing and Electronic Commerce 20 (3): 213–233.

    Article  Google Scholar 

  • Kirsch, L.J., Sambamurthy, V., Ko, D.-G. and Purvis, R.L. (2002). Controlling Information Systems Development Projects: The view from the client, Management Science 48 (4): 484–498.

    Article  Google Scholar 

  • Kossinets, G. (2006). Effects of Missing Data in Social Networks, Social Networks 28 (3): 247–268.

    Article  Google Scholar 

  • Kotlarsky, J. and Oshri, H. (2005). Social Ties, Knowledge Sharing and Successful Collaboration in Globally Distributed System Development Projects, European Journal of Information Systems 14 (1): 37–48.

    Article  Google Scholar 

  • Levina, N. and Vaast, E. (2005). The Emergence of Boundary Spanning Competence in Practice: Implications for implementation and use of information systems, MIS Quarterly 29 (2): 335–363.

    Google Scholar 

  • Levina, N. and Vaast, E. (2006). Turning a Community into a Market: A practice perspective on IT use in boundary spanning, Journal of Management Information Systems 22 (4): 13–37.

    Article  Google Scholar 

  • Luftman, J., Zadeh, H.S., Derksen, B., Santana, M., Rigoni, E.H. and Huang, Z. (2013). Key Information Technology and Management Issues 2012–2013: An international study, Journal of Information Technology (Palgrave Macmillan) 28 (4): 354–366.

    Article  Google Scholar 

  • Lynch, T. and Gregor, S. (2004). User Participation in Decision Support Systems Development: Influencing system outcomes, European Journal of Information Systems 13 (4): 286–301.

    Article  Google Scholar 

  • Maes, R. (1999). A generic framework for information management, [www document] http://imwww.fee.uva.nl/~pv/PDFdocs/99-03.pdf (accessed 24 August 2011).

  • Markus, M.L. and Mao, J.-Y. (2004). Participation in Development and Implementation – Updating an old, tired concept for today’s IS contexts, Journal of the Association of Information Systems 5 (11/12): 514–544.

    Google Scholar 

  • Misztal, B.A. (1996). Trust in Modern Societies: The search for the bases of social order, Cambridge: Polity Press.

    Google Scholar 

  • Myers, M.D. and Newman, M. (2007). The Qualitative Interview in IS Research: Examining the craft, Information and Organization 17 (1): 2–26.

    Article  Google Scholar 

  • Nahapiet, J. and Ghoshal, S. (1998). Social, Capital, Intellectual Capital and the Organizational Advantage, Academy of Management Review 23 (2): 242–266.

    Google Scholar 

  • Nelson, K.M. and Cooprider, J.G. (1996). The Contribution of Shared Knowledge to IS Group Performance, MIS Quarterly 20 (4): 409–432.

    Article  Google Scholar 

  • Nonaka, I. (1994). A Dynamic Theory of Organizational Knowledge Creation, Organization Science 5 (1): 14–37.

    Article  Google Scholar 

  • Orlikowski, W.J. (2002). Knowing in Practice: Enacting a collective capability in distributed organizing, Organization Science 13 (3): 249–273.

    Article  Google Scholar 

  • Peppard, J. (2007). The Conundrum of IT Management, European Journal of Information Systems 16 (4): 336–345.

    Article  Google Scholar 

  • Peppard, J. and Ward, J.M. (2004). Beyond Strategic Information Systems: Towards an IS capability, Journal of Strategic Information Systems 13 (2): 167–194.

    Article  Google Scholar 

  • Persson, J.S., Mathiassen, L. and Aaen, I. (2012). Agile Distributed Software Development: Enacting control through media and context, Information Systems Journal 22 (6): 411–433.

    Article  Google Scholar 

  • Pozzebon, M. and Pinsonneault, A. (2012). The Dynamics of Client–Consultant Relationships: Exploring the interplay of power and knowledge, Journal of Information Technology, (Palgrave Macmillan) 27 (1): 35–56.

    Article  Google Scholar 

  • Preston, D.S. and Karahanna, E. (2009). Antecedents of IS Strategic Alignment: A nomological network, Information Systems Research 20 (2): 159–179.

    Article  Google Scholar 

  • Rai, A., Maruping, L.M. and Venkatesh, V. (2009). Offshore Information Systems Project Success: The role of social embeddedness and cultural characteristics, MIS Quarterly 33 (3): 617–642.

    Google Scholar 

  • Reich, B.H. and Benbasat, I. (2000). Factors that Influence the Social Dimension of Alignment between Business and Information Technology Objectives, MIS Quarterly 24 (1): 81–113.

    Article  Google Scholar 

  • Reynolds, T.J. and Gutman, J. (1988). Laddering Theory, method, Analysis and interpretation, Journal of Advertising Research 28 (1): 11–31.

    Google Scholar 

  • Rose, J. and Schlichter, B.R. (2013). Decoupling, Re-engaging: Managing trust relationships in implementation projects, Information Systems Journal 23 (1): 5–33.

    Article  Google Scholar 

  • Rugg, G. and McGeorge, P. (1995). Laddering, Expert Systems 12 (4): 339–346.

    Article  Google Scholar 

  • Saldaña, J. (2011). The Coding Manual for Qualitative Researchers, reprint. edn., Los Angeles: Sage Publications.

    Google Scholar 

  • Sasidharan, S., Santhanam, R., Brass, D.J. and Sambamurthy, V. (2012). The Effects of Social Network Structure on Enterprise Systems Success: A longitudinal multilevel analysis, Information Systems Research 23 (3-part-1): 658–678.

    Article  Google Scholar 

  • Schrott, G. and Beimborn, D. (2003). Informal Knowledge Networks: Towards a community-engineering framework, in 24th International Conference on Information Systems (ICIS) (Seattle, WA).

  • Schultze, U. and Avital, M. (2011). Designing Interviews to Generate Rich Data for Information System Research, Information and Organization 21 (1): 1–16.

    Article  Google Scholar 

  • Schwarz, A. and Hirschheim, R. (2003). An Extended Platform Logic Perspective of IT Governance: Managing perceptions and activities of IT, Journal of Strategic Information Systems 12 (2): 129–166.

    Article  Google Scholar 

  • Seddon, P.B., Calvert, C. and Yang, S. (2010). A Multi-project Model of Key Factors Affecting Organizational Benefits from Enterprise Systems, MIS Quarterly 34 (2): 305–328.

    Google Scholar 

  • Shuraida, S. and Barki, H. (2013). The Influence of Analyst Communication in IS Projects, Journal of the Association for Information Systems 14 (9):Article 9.

  • Soh, C., Chua, C.E.H. and Singh, H. (2011). Managing Diverse Stakeholders in Enterprise Systems Projects: A control portfolio approach, Journal of Information Technology 26 (1): 16–31.

    Article  Google Scholar 

  • Sun, Y., Fang, Y., Lim, K.H. and Straub, D. (2012). User Satisfaction with Information Technology Service Delivery: A social capital perspective, Information Systems Research 23 (4): 1195–1211.

    Article  Google Scholar 

  • Tallon, P.P. and Pinsonneault, A. (2011). Competing Perspectives on the Link between Strategic Information Technology Alignment and Organizational Agility: Insights from a mediation model, MIS Quarterly 35 (2): 463–486.

    Google Scholar 

  • Tanriverdi, H. (2005). Information Technology Relatedness, Knowledge Management Capability and Performance of Multibusiness Firms, MIS Quarterly 29 (2): 311–334.

    Google Scholar 

  • Tanriverdi, H. and Venkatraman, N. (2005). Knowledge Relatedness and the Performance of Multi-business Firms, Strategic Management Journal 26 (2): 97–119.

    Article  Google Scholar 

  • Tarafdar, M. and Qrunfleh, S. (2009). IT-business Alignment: A two-level analysis, Information Systems Management 26 (4): 338–349.

    Article  Google Scholar 

  • Tarafdar, M. and Qrunfleh, S. (2010). Examining Tactical Information Technology-business Alignment, Journal of Computer Information Systems 50 (4): 107–116.

    Google Scholar 

  • Tiwana, A. (2008). Do Bridging Ties Complement Strong Ties? An Empirical Examination of Alliance Ambidexterity, Strategic Management Journal 29 (3): 251–272.

    Article  Google Scholar 

  • Tiwana, A. and Konsynski, B. (2010). Complementarities between Organizational IT Architecture and Governance Structure, Information Systems Research 21 (2): 288–304.

    Article  Google Scholar 

  • Tiwana, A. and McLean, E.R. (2005). Expertise Integration and Creativity in Information Systems Development, Journal of Management Information Systems 22 (1): 13–43.

    Google Scholar 

  • Tortoriello, M., Reagans, R. and McEvily, B. (2012). Bridging the Knowledge Gap: The influence of strong ties, network cohesion, and network range on the transfer of knowledge between organizational units, Organization Science 23 (4): 1024–1039.

    Article  Google Scholar 

  • Tushman, M.L. (1977). Special Boundary Roles in the Innovation Process, Administrative Science Quarterly 22 (4): 587–605.

    Article  Google Scholar 

  • Valorinta, M. (2011). IT Alignment and the Boundaries of the IT Function, Journal of Information Technology 26 (1): 46–59.

    Article  Google Scholar 

  • van den Hooff, B. and de Winter, M. (2011). Us and Them: A social capital perspective on the relationship between the business and IT departments, European Journal of Information Systems 20 (3): 1–12.

    Article  Google Scholar 

  • Walentowitz, K. and Beimborn, D. (2011). The Social Antecedents of Business/IT Alignment: Reviewing the role of social network structure in alignment research, International Journal of IT/Business Alignment and Governance (IJITBAG) 2 (2): 15–32.

    Article  Google Scholar 

  • Ward, J. and Peppard, J. (1996). Reconciling the IT/Business Relationship: A troubled marriage in need of guidance, Journal of Strategic Information Systems 5 (1): 37–65.

    Article  Google Scholar 

  • Wasserman, S. and Faust, K. (2007). Social Network Analysis: Methods and Applications, Cambridge: Cambridge University Press.

    Google Scholar 

  • Willcoxson, L. and Chatham, R. (2004). Progress in the IT/Business Relationship: A longitudinal assessment, Journal of Information Technology 19 (1): 71–80.

    Article  Google Scholar 

  • Yin, R.K. (2009). Case Study Research: Design and Methods, 4th edn, Thousand Oaks: Sage Publications.

    Google Scholar 

  • Zolper, K., Beimborn, D. and Weitzel, T. (2013). When the River Leaves its Bed: Analyzing deviations between planned and actual interaction structures in IT change processes, Journal of Information Technology 28 (4): 333–353.

    Article  Google Scholar 

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Correspondence to Daniel Beimborn.

Appendices

Appendix A

Interview guideline

  • Background of interviewee: Personal background? Cross-domain experience? Role in the application change process?

  • General network structure: Please draw the general interaction structure as you perceive it in the application change process. Please rate the amount and intensity of interaction between the involved units. Next, describe the relationship structure (i.e., trust, etc.) in the same way.

  • Existence of interface actors: Do you interact with the other unit? Are there any actors in the other unit that you interact with in particular?

  • Applying laddering: How does this situation (e.g., the existence of a particular counterpart in the IT) influence the application change process? Why is it important?

  • Relationship contents to the other unit (if person is interface actor): How would you characterize your relationship to the IT unit/business unit?

  • Analysis of relationship contents: How does this particular relationship-content help/hinder you in realizing changes? Why is that important? How did this characteristic develop?

  • Relationship content within the unit: Characterize the relationship structure within your unit.

  • Analysis of relationship contents as described above.

  • Success factors: What are the success factors in the application change process? (If these were social structures or relationship contents, apply the same approach as described above.)

  • Application change effectiveness: How would you evaluate the IT change process? Are changes implemented in a way that is beneficial for the business? Does IT add value during the IT change process in addition to merely implementing? Are changes implemented on time?

Appendix B

Laddering

The laddering approach offers a structured interviewing technique that facilitates soliciting knowledge from experts (e.g., Corbridge et al., 1994; Rugg and McGeorge, 1995) or identifying means-ends relationships (Reynolds and Gutman, 1988). It uses a small number of questions and thereby elucidates the relationship between concepts (Corbridge et al., 1994). These questions aim at drilling deeper into and thus building a ladder along the reasoning of the interviewee (Reynolds and Gutman, 1988). This interviewing technique results in more systematic answers, richer insights, and more control by the researcher over the interview even when discussing an unstructured or complex topic (Rugg and McGeorge, 1995). Examples for questions to identify causal relationships used in our interviews are ‘How did this particular relationship content (e.g., trust) help you when dealing with this change?’ or when the answer was that ‘I can come more directly to the point’ a follow-up probe might be ‘Why could you come more directly to your point based on your trusted relationship.’

Appendix C

Ensuring reliability and validity

Table C1

Table C1 Procedures for high quality data collection (based on Yin (2009))

Appendix D

Questionnaire for SNA

(1a) Please indicate employees from the business unit with whom you interact a lot in the context of the application change process for System XY and describe how often you interact with them via which channel.

illustration

figure b

(1b) <during the interview> Please rate the following three statements regarding each person you have named in the questionnaire before this interview on a scale from 1 to 7, 1 meaning ‘I totally disagree’ and 7 meaning ‘I fully agree.’

illustration

figure a

(2a) Please indicate employees from the IT unit with whom you interact a lot in the context of the application change process of System XY and describe how and how often you interact with them.

<answered within the same type of table as question 1>

(2b) <analogous procedure as in (1b) regarding colleagues in the IT unit>

Appendix E

Table E1

Table E1 Descriptive SNA statistics

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Zolper, K., Beimborn, D. & Weitzel, T. The effect of social network structures at the business/IT interface on IT application change effectiveness. J Inf Technol 29, 148–169 (2014). https://doi.org/10.1057/jit.2014.6

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