Analysis of thedevelopment and diffusion of technological innovations in oil spill forecasting: The MEDESS-4MS case

Deep-Sea Research II ∎ (∎∎∎∎) ∎∎∎–∎∎∎

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Deep-Sea Research II

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Regular article

Analysis of the development and diffusion of technological innovationsin oil spill forecasting: The MEDESS-4MS case$

Alberto Marcati a,n, M. Irene Prete b, Antonio Mileti b, Mario Cortese c, George Zodiatis d,Andria Karaolia d, Adam Gauci e, Aldo Drago e

a Department of Business and Management, LUISS Guido Carli, Viale Romania, 32, 00197 Rome, Italyb Department of Management, Economics, Mathematics and Statistics, University of Salento, Ecotekne Campus, 73100 Lecce, Italyc Department of Business and Management, Buckinghamshire New University, Queen Alexandra Road, HP11 2JZ, High Wycombe, UKd Oceanography Center, University of Cyprus (OC-UCY), Nicosia, Cypruse Physical Oceanography Research Group, Department of Geosciences, Faculty of Science, University of Malta, Malta

a r t i c l e i n f o

Keywords:Oil spillsTechnology transferPredictionMarketingModelsMarine environment

x.doi.org/10.1016/j.dsr2.2016.05.02545/& 2016 Elsevier Ltd. All rights reserved.

ESS-4MS is the acronym of MediterraneanSafety.espondence to: LUISS Guido Carli, Viale Romaail address: [email protected] (A. Marcati).

e cite this article as: Marcati, A., easting: The MEDESS-4MS case. Deep

a b s t r a c t

This paper presents a case study on the management of users’ engagement in the development of anew technology. Based on the experience of MEDESS-4MS, an integrated operational model for oilspill Decision Support System covering the whole Mediterranean Sea, the case study is aimed at thedevelopment of a framework for user engagement and for the management of its dual logic. Indeed,users may play a dual role in the innovation process, contributing to both the design of the innovationand its promotion. Users contribute to shaping the innovation, by aggregating and integratingknowledge, and they facilitate its diffusion, by adopting the innovation and fostering its adoption withinthe socio-economic system.

& 2016 Elsevier Ltd. All rights reserved.

1. Introduction

This paper centers on the development stage and early intro-duction of a technological innovation and presents a case studyabout the management of users’ engagement in such an occur-rence, on the basis of evidence coming from research concerningthe design and the development of innovations. In particular, thecase study examines how users have been engaged in the devel-opment of a new technology for oil spills emergencies, theMEDESS-4MS (Mediterranean Decision Support System for MarineSafety) model.

MEDESS-4MS is dedicated to the strengthening of maritimesafety, by mitigating the risks and impacts associated with oilspills. It capitalizes on existing frameworks developed at Europeancountry level and at the Mediterranean level with MONGOOS(Mediterranean Oceanography Network for Global Ocean Obser-ving System), and embraces recent advances and developments inoceanography for the Mediterranean area. It delivers an integratedoperational model for oil spill forecasting in the Mediterranean, bygathering and analyzing met-ocean data as well as data related to

Decision Support System for

nia, 32, 00197 Rome, Italy.

t al., Analysis of the deve-Sea Res. II (2016), http://d

ship traffic, ship operations and sensitivity mapping. It also pro-vides a few services to assist operational response agencies; inparticular, oil spill forecasts originating from satellite observationsof oil slick, oil spill simulations using historical met-ocean data,and, finally, oil spill simulations in real time, to deal with the realtime management of emergencies. Therefore, it offers an innova-tive and up-to-date technological system to deal with oil spillemergencies (Fig. 1).

For a detailed account of MEDESS-4MS, refer to Zodiatis et al.(2016), this DSRII, Special Issue.

We present here the paper as follows:

� In the next section (2. The theoretical framework), we draw thetheoretical framework about the general process of adoption ofthe innovation into the target socio-economic system;

� In the following section (3. The main actors), we introduce theMEDESS-4MS case study by analyzing the roles, the objectivesand the strategies of the actors populating the socio-economicsystem that characterizes oil spill management;

� In the following section (4. The engagement part 1), we reportabout the insights received by stakeholders and end users inorder to design the technological innovation;

� In the following section (5. The engagement part 2), we informabout the way all the players have been involved in the processof interaction;

lopment and diffusion of technological innovations in oil spillx.doi.org/10.1016/j.dsr2.2016.05.025i

www.sciencedirect.com/science/journal/09670645

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http://dx.doi.org/10.1016/j.dsr2.2016.05.025



mailto:[email protected]





Fig. 1. The MEDESS-4MS web portal.

A. Marcati et al. / Deep-Sea Research II ∎ (∎∎∎∎) ∎∎∎–∎∎∎2

� In the last section (6. Conclusions), we draw a number ofconclusions on the development and diffusion of technologicalinnovations in oil spill forecasting and the MEDESS-4MS case.

2. The theoretical framework

Previous research showed how technology and markets oftenevolve independently, in unpredictable ways (Freeman, 1984), andat times conflict. The world of technology developers and oftechnology users often diverge and do not interact, at least at thebeginning. It may happen, therefore, that even breakthrough orvery beneficial and advantageous innovations do not find theirway to markets, so that innovative technologies, or “technicalobjects” as they came to be known (Akrich et al., 1988, 2002;Gaillard, 2000), fail to provide value to their intended users. Sev-eral innovations keep a marginal position within the market, and,unable to “cross the chasm” (Moore, 1991), the discontinuityexisting between “technological” expert users and “non-techno-logical” novices, are not used as extensively and intensively as theyshould (Shih and Venkatesh, 2004).

To develop successful innovations, organizations need to bringtechnology and markets close together, by acting simultaneouslyon the technological and socio-economic sides of the system. Theprocess of penetration into the market is not mono-directional,from the organization to the market, and the model that accountsfor such a process is not based on the diffusion of a well formedproduct, defined in all its aspects. It is instead a bi-directional,spiraling, “whirlwind” process of interaction, where the product orservice takes shape in an interaction between the organizationsand the market (Akrich et al., 1988, 2002). It is a collective process,where individuals and organizations mix together, for the gen-eration and development of knowledge; where agents of variouskind (inventors or creators, users, stakeholders) are interactingand developing innovative solutions; where resources of differentkind, intellectual and social capital, are mobilized to create anddevelop knowledge and to shape innovations.

Please cite this article as: Marcati, A., et al., Analysis of the deveforecasting: The MEDESS-4MS case. Deep-Sea Res. II (2016), http://d

In such a framework, the market – the targeted socio-economicsystem – plays a strategic role as a “force” driving and shaping theinnovation itself, as a driver of discovery and aggregation and as amold for the innovation to be. Users play an active role becausethey contribute to the development of the innovation, by aggre-gating and integrating knowledge about needs, applications, andusages (Rosenzweig et al., 2003; Urban and von Hippel, 1988; vonHippel, 1986). But, they also play an active role because, byadopting the innovation, they influence further adoption by imi-tators and followers (Rogers, 2003).

Indeed, the diffusion of innovations is usually modeled as aprocess, where the most innovative users play a leading role andpromote and trigger the further adoption of the innovation byother organizations or individuals (Van den Bulte and Joshi, 2007).

Successful innovations usually result from the interactionbetween providers and users, and a rich empirical evidence showsthat products or services launched in the market undergo subse-quently deep changes and are adapted to the emerging needs ofthe market: “the movement of adoption is a movement of adap-tation” (Akrich et al., 2002, p. 209). The key for success is, there-fore, attained by increasing dialogue with and among the usersthat better represent the needs of the market and may stimulatean understanding of those needs and related usages. In particular,“the success of an innovation may be explained …by its capacity tocreate adhesion between numerous allies (users, intermediaries,etc.)” (Akrich et al., 2002, p. 208) and “the fate of innovation, itscontent but also its chances of success, rest entirely on the choiceof the representatives or spokespersons who will interact andnegotiate to give shape to the project and to transform it until amarket is built” (Akrich et al., 2002, p. 217).

To manage successfully such a process, organizations have to:

1. Identify and select the right “spokespersons”, individuals ororganizations.Customers and users are often instrumental to the generationand adoption of innovations and play a variety of roles in such aprocess. They may be the (passive) source of insights, about





A. Marcati et al. / Deep-Sea Research II ∎ (∎∎∎∎) ∎∎∎–∎∎∎ 3

their needs, perceptions, attitudes, preferences and behaviors.But they may also be the (active) source of solutions, as leadusers, that face needs that will spread in the future marketplace(Urban and von Hippel, 1988; von Hippel, 1986). Depending ontheir capabilities and motivations (Lüthje and Herstatt, 2004),users may play these different roles and may act as “spokes-persons” for all the potential users that belong to the system.Therefore, by interacting with innovative organizations, usersmay take part in the process of innovation generation and mayhelp shaping the innovation by adapting it to their needs andrequirements (Coviello and Joseph, 2012). In addition to this,they may also be the early adopters that trigger the process ofpenetration and diffusion within the market and the socio-economic system (van den Bulte and Joshi, 2007).

2. Foster “spokespersons” engagement into the innovationprocess.

It is widely recognized that exchanges and relations amongindividuals and organizations are affected by factors such as“structural features” (i.e., duration and longevity, intensity andbreadth, symmetry and mutual dependence) and “positive atmo-spheres” (i.e., cooperation, trust, understanding, closeness, com-mitment) (Anderson et al., 1994; Brodie et al., 2011; Dwyer et al.,1987; Hunt, 1994; Ulrich, 1989). To take fully advantage of thecontributions of individuals or organizations, it is very importantto gain their engagement. Engagement is a multidimensionalconcept subject to a context- and/or stakeholder-specific expres-sion (Brodie et al., 2011; Calder et al., 2013; Hollebeek, 2011; vanDoorn et al., 2010; Verhoef et al., 2009), that depends on inter-active customer experiences and develops through interactiveprocesses. Hence, to foster the engagement of end users, organi-zations have to provide primarily a positive user's experience. But,they need also to establish strong relations, based upon favorable“structural features” and “positive atmospheres”.

3. The main actors – stakeholders and users, specialists andgeneralists

First of all, we identify the relevant actors, i.e., potential sta-keholders and end users, and analyze their organizational char-acteristics and activities, in order to understand their involvementwith oil spills and their interest in models such as MEDESS-4MS.The objective is to gather insights on their usage of this or similarmodels and services and to understand the main value drivers ableto get them more involved. By ensuring that the main value dri-vers are captured and fed into the process, we guarantee thatusers’ needs, expectations and requirements are reflected in thedevelopment of the new product, and we also encourage theirsupport to innovating it.

The analysis begins with the recognition of a selected numberof key stakeholders. Stakeholders are here defined as “the groupsor the individuals who can affect or be affected by the achieve-ments of an organization” (Craig Smith et al., 2010; Freeman, 1984)and can represent the foundation of a potential wider network ofinterested and relevant partners. Especially in the provision ofservices, organizations should reach out beyond the limits andboundaries provided by users and remember that “multiple sta-keholders are involved,… and value cannot be created in isolationof the stakeholders” (Lusch, 2007, p. 266).

Through a first, exploratory, survey we aim at understandingthe importance for stakeholders and users of oil spill relatedactivities and the role that these activities play within the orga-nizations concerned, the position that these activities hold withinthe overall Value Chain (or system of activities), and the impor-tance given to oil spill forecasting.


The purpose of the survey is to build a “profile” of the users,beyond their specific involvement in oil spills, to understand theiractual or potential interest for oil spill forecasting, and to accountfor the heterogeneity in their approaches. The building of userprofiles is motivated by the need to grasp users’ differences inpreferences, interests, goals, background skills and socio-economiccontexts. Discovering these differences is vital to understandingthe importance they assign to information and services.

The most significant stakeholders and users form the backboneof the oil spill Value Chain, i.e., the integrated system of activitiesrelated to the prevention and preparedness, emergency response,recovery and restoration of oil spills (Porter, 1985). They are:

1. IMO – The International Maritime Organization is a specializedagency of the United Nations, whose primary purpose is todevelop and maintain a comprehensive regulatory frameworkfor shipping: its remit today includes safety, environmentalconcerns, legal matters, technical cooperation, maritime secur-ity and the efficiency of shipping.

2. IOPC Funds – The International Oil Pollution CompensationFunds are intergovernmental organizations that provide finan-cial compensation for oil pollution damage resulting from spillsof persistent oil from tankers.

3. EMSA – The European Maritime Safety Agency is an agencyassisting the European Commission in monitoring the imple-mentation of EU legislation relating, among others, to shipconstruction and planned maintenance, ship inspection and thereception of ship waste in EU ports, certification of marineequipment, ship security, the training of seafarers in non-EUcountries and Port State Control.

4. ITOPF – The International Tanker Owners Pollution Federation isa not-for-profit organization established on behalf of theworld's ship-owners to promote an effective response to marinespills of oil, chemicals and other hazardous substances. TheFederation provides objective technical advice and informationon all aspects of pollution response and the effects of spills onthe marine environment.

5. IPIECA – The International Petroleum Industry EnvironmentalConservation Association is the global oil and gas industryassociation for environmental and social issues. IPIECA wasformed following the launch of the United Nations EnvironmentProgramme (UNEP) and is the only global association involvingboth the upstream and downstream oil and gas industry onenvironmental and social issues with memberships coveringover half of the world's oil production.

6. Sea Alarm – A Public Foundation that coordinates professionalresponses to oil-based wildlife contingencies. Working in closecollaboration with non-governmental organizations (NGOs),government authorities and the oil and maritime industries,Sea Alarm initiates and facilitates strategic response and pre-paredness activities to oil-based contingencies.

7. REMPEC – The Regional Marine Pollution Emergency ResponseCentre for the Mediterranean Sea is administered by the Inter-national Maritime Organization (IMO) in cooperation withUNEP/MAP.

Oil spills management is, in general, the responsibility ofnational and international institutions. The key end users of theMEDESS-4MS model will be, indeed, public and institutionalbodies, intergovernmental or governmental entities, local autho-rities, such as Coast Guards, Maritime Safety Departments, PortAuthorities, Local or Regional Governments. Moreover, there arealso several private end users engaged in oil spill prevention andpossibly interested in MEDESS-4MS for private use: internationalassociations, such as IPIECA, ITOPF, IOPC; private companiesoperating in the oil and gas industry, marine exploration and






offshore industry, oil spill prevention and emergency response.Furthermore, several other organizations may become interestedin the forecasting and management of oil spills, when these latteroccur: for instance, tourism sector companies; fishing and aqua-culture companies; organizations involved in environmentallysensitive areas, e.g., marine parks.

This is a very fragmented and heterogeneous set of organiza-tions, although the empirical evidence currently available brings tobelieve that the system is polarized and split into two completelydifferent groups of organizations, and that there is a cleavagebetween “specialists” and “generalists”.

Awareness and concern for oil spills is concentrated within alimited number of organizations – so called “specialists” – thatcarry institutional obligations about oil spills or that are directlyand tightly related to oil spill events, because these eventsrepresent their main or key area of activity. Indeed, these organi-zations may be dedicated exclusively to the management of oilspills (as REMPEC) or may have oil spills as an important focus ofactivity. These organizations may take a very different form and beeither public (as EMSA, the Coast Guard, the Port Authorities) orprivate (as IPIECA, ITOPF, IOPC Funds, again some of the PortAuthorities, businesses belonging to the “oil spill industry”,environmental groups, and similar). On the contrary, other orga-nizations – the so called “generalists” –may be involved either as apotential source of spills (shipping companies, companies involvedin the production and refinery of oil and gas) or as a target of oilspills, because they may be affected by spills (Governments, fish-ing companies, companies active in the tourism sector, marineparks). “Generalists” show a more superficial involvement with oilspill management and are less concerned with the forecasts of oilspills. They get activated only in case of specific events, when thethreat of oil spills becomes more real and/or the impact stronger.

This lack of interest may be determined, at least partially, bythe decreasing number of spills and by the evolution of the phe-nomenon. In particular, the phenomenon is somehow split intotwo completely different kind of events: a few spills with a largeimpact and low likelihood of occurrence, on the one hand, and avery large number of small scale and limited spills, with a highlikelihood of occurrence, but a localized impact, on the other hand.So, those among the “generalists” that have no specific responsi-bility to deal with the more severe (Tier 3) spills, do not seem to bestrongly interested in them.

To conclude the analysis, the “specialists” form the “hub” of thenetwork, a very concentrated network, populated by a smallnumber of organizations that play a leading role within the oilspills Value Chain and have developed stable and collaborativerelationships, at least at national level. This network is composedby further, smaller, “networks” of organizations, that have devel-oped over the years relations so tight, that it is difficult to disen-tangle the influences and positions, orientations and strategies ofthe single organizations. As an example it is possible to refer to theItalian case, where the Italian Coast Guard (ITCG), with its localunits (Capitanerie di Porto), interacts with the Italian Ministry forthe Environment (Ministero dell’Ambiente) and, funded by thelatter, plays a leading role for the marine safety and the preventionof marine pollution. But, in case of major emergencies, the ItalianCoast Guard also interacts with both the Italian Civil Protection(Protezione Civile) and Castalia, a private consortium of equipmentoperators involved into the management of spills, that has stipu-lated specific agreements with the Italian Ministry for Environ-ment and is under the guidance of the Coast Guard. “Generalists”,on the contrary, form the periphery of the network also known asthe “tail” of the distribution (Andersson, 2004). They are a muchwider and fragmented set of heterogeneous and loosely relatedorganizations, becoming interested into oil spill only in case ofspecific events. Therefore, our analysis shows that oil spill


forecasting and management is an issue only for organizationsthat operate on emergency response within the boundaries of asingle country, with a limited geographical scope. None (exceptEMSA and REMPEC) spans across the whole Mediterranean,although instances of cooperation are emerging, involving smallgroups of countries.

4. The engagement part 1 – Fine tuning the product

As it has been already pointed out, the case study provides ananalysis of the requirements of stakeholders and users and of thechanges and improvements they consider important. Dependingon this assessment, each component of the Decision SupportSystem can be implemented in an enhanced service offering, inorder to provide users with more valuable and personalizedsolutions. To this end, we design and realize two additional sur-veys. The first one takes a quantitative approach and investigatesusers requirements strictly related to the basic features of themodel; the second one takes a qualitative and quantitativeapproach, to get from professional users a broader evaluation ofthe model, geared towards an operational usage.

Based on the information collected, users seem to be, onaverage, in the “thick of things”, deeply embedded within thesystem of management of oil spills and well connected to the restof the system. They appear to be also well organized and endowedwith resources and with the capability to deal with the differentaspects of oil spills. For instance, many organizations have unitsdesigned to cope with oil spills and have already drawn oil spillemergency plans; several actors use equipment to deal with oilspills (skimmers, booms and similar). In general, good practicesare widespread, although not yet universally implemented. But, asorganizations are heterogeneous and adopt different approaches,their attitudes and behaviors are somehow dispersed and varied,even when they play the same role and fill the same positionwithin the system. Nonetheless, the concurrent existence of moreorganizational units involved in oil spill management, the rele-vance of contingency plans and the ownership of equipment aresomehow related and clustered together, associated to the specificuser's involvement in emergency response.

As far as forecasts are concerned, users in our sample recognizea key role to forecasting systems and attribute a high impact toforecasting; nonetheless, their use of forecasts is in general ratherhaphazard and not well structured. Only few of them have accessto oil spill forecasting for monitoring and decision-making; whenthey engage in it, they appear to be stepping up a sort of home-made “bricolage”, relying on multiple, and largely public, provi-ders of met-oceanographic forecasts.

Our analysis focuses on the features of the Decision SupportSystem that have an impact on the “Value Proposition”, i.e. the setof benefits or advantages that can be delivered by the DecisionSupport System, and also on the aspects that may help improvingthe working of the system and its performance. These aspects havea differential impact and influence on both the process of oil spillmanagement and the oil spill Value Chain, and are differentlybeneficial to the functions performed by the users (see Table 1).

It can be inferred that respondents favor aspects that are usefulfor operations and help the management of emergencies, oncespills have occurred. Aspects that result in better forecasting andmake the forecasts more accurate are deemed extremely useful bythe respondents. The attention of users is, first of all, on the speedof response (less than 30 min since the first warning), with timelyand frequently repeated forecasts (every hour).

There is an interest in features that help forecasting the evo-lution of the oil spills in the short term, and its likely impact on theshoreline. Furthermore, there is an interest in features that make






information easier to understand, description of the oil spill evo-lution more vivid (i.e. oil spill location, mete-ocean forecasts) andunderstanding of the oil spill evolution more accessible. Con-versely, there is very little interest on information on long termforecasts and on the Bonn Agreement Oil Appearance Code(BAOAC) – a “code” that refers to the relationship between thevisual appearance of oil on the sea surface and that contributes toestimate spilled oil volume, given the thickness of the oil layer (seeFig. 2).

It must be pointed out also that users do not show a commonapproach or attitude towards forecasting and no aspect of theforecasting system draws a common response. As one wouldexpect, evaluations vary widely and rankings differ acrossrespondents, because individual users deal with the matter dif-ferently and weigh differently each aspect, according to their ownfunctions. The analysis confirms that heterogeneity is widespread,but some homogeneity exists within categories, and patternsemerge when users belonging to the same category share func-tions and activities, approaches and interests concerning the sameissues.

“Generalists” show a more heterogeneous approach to oil spillmanagement than “specialists”. This can be explained by theirheterogeneous objectives, partly different from those of “specia-lists”. In particular, they see oil spill management as a relevantactivity for keeping the company compliant with industry stan-

123Table 1

Features affecting the value of the Decision Support System.

Basic features

Oil spill location Oil spill source Early warning identifica-tion of shoreline impact

Oil spill area (surface) Meteo and Oceano-graphic forecasts

Oil spill forecasts up to12/24/48/72 hours

Oil spill volume Meteo and Oceano-graphic data analysis

Frequency of forecasts

Bonn Agreement OilAppearance Code

Oil spill movementforecasts

Speed of response

Pollutant type Oil spill fate forecasts Spatial resolution

Fig. 2. Evaluation of


dards, and their objectives are mainly driven by legal or institutionalrequirements (see Fig. 3). As already argued previously, “generalists”often do not perceive the need for monitoring marine operationsconstantly, since the risk of oil spills is perceived as very low; but,they are focused on having in place procedures, which enable themboth to be legally and institutionally compliant and to deal with“the worst case scenario”, in case it happens.

On the contrary, it is possible to see more homogeneity among“specialists”. For instance, Ports Authorities share a lack of interestfor oil spill location, thickness and source, together with BonnAgreement Oil Appearance Code as well as pollutant type, andassign more value to forecasts of oil spill movements and fate,met- and oceanographic analyses, identification of shorelineimpact, forecasts up to 12 h. This may be explained by the fact thatthey are at the end of the process of oil spill management and areespecially interested in the destination of the oil spill. To highlightboth the common aspects and the individual differences, specificdata for individual Port Authorities and average data for the groupare displayed in Fig. 4.

Given the diversity in objectives and usage, a preliminaryanalysis of users’ key requirements is due. For this purpose, a set ofpromising product features has been identified by relating to itemsbelonging to similar models available in the market. This bench-marking approach led to the definition of key features classified inthree core areas:

) the model intrinsic characteristics,) the software usability,) the technical service levels.

Model-related features are strictly related to the functioning ofthe predictions. Given that predictions are designed to understandthe transport, fate and weathering of an oil spill, model-relatedfeatures describe the extent to which the prediction can be pre-cise, conveniently executed and easily handled by end users.

Software-related features describe the software usage, interfaceand data management. These features are relevant because theyare the vehicle whereby the model conveys data and informationon oil spill predictions. In this domain, features are not necessarilyincluded in a single, tightly integrated, solution, but can take the

basic features.





Fig. 3. Percentage of “generalist” end users supporting the cited objectives.

Fig. 4. Evaluation of basic and extended features by Port Authorities.


form of multiple software solutions (e.g., data storage and dataprotection can be included in two different software solutions).Furthermore, these software tools can interact with the existinginformation technology infrastructure of the user. For all thesereasons, users are deeply concerned with the resources that arespent on them.

Service-related features represent a “service-pack”, consistingof a collection of training sessions, various types of technicalsupport, updates, and enhancements of both the model and thesoftware. They are usually part of a service-level agreement sti-pulated by the provider/s and user/s of the Decision SupportSystem.

Table 2 summarizes the main product features available.Once the main features are recognized, we examine the value

perceived by users about each of them. The results of this analysisare presented in the Figs. 5–7. Within the first set of features,geographic definition, real-time forecasting and spatial resolutionare considered of higher value. Within the second set, ease of useof the software and its ergonomics are the most important fea-tures; moreover, adaptability, warning systems and compatibilityare deemed relevant as well. Within the third set, training is highlyrelevant as well as technical support on-demand.

Finally, the analysis points to major improvements to the sys-tem. As Fig. 8 shows, value can be increased by adding completelynew features. Deeper changes have been explored, across a num-ber of different directions, and their impact on the value of theDecision Support System for end users has been investigated.


Some of these changes, while improving the forecasting abilityof the model and affecting its value, do not modify significantly itsstructure. Changes of this kind are the following:

1. Specification of oil weathering processes;2. Customization of the user interface;3. Improvement of the database of oil types;4. Provision of an interface between satellite and in situ data.

Other changes require a deep re-structuring of the model, byadding more specific and heterogeneous components to themodel, in order to broaden its functioning and outcomes. Changesof this kind are the following:

1. Stochastic forecasts;2. Subsurface release;3. Backtracking;4. Information about local resources;5. Information about impact;6. Customized, local forecasts;7. Simulation of different response options.

The relevance of these changes differs widely. The most rele-vant appear to be: (1) simulation in an emergency, (2) customizedhazard risk map, (3) geo-localization of oil spill response, (4) goo-gle map visualization, and (5) forecasting in oil transport. On thecontrary, the less relevant changes are: (1) generic simulation,





Table 2Features of different components of the offer.

Model-related features Software-related features Service-related features

1. Overall model quality 1. Database with historical data 1. Provision of exercises and training tools2. Real-time forecasts 2. Ease of use of the software 2. Training sessions3. Spatial resolution 3. Software ergonomics 3. 24-hours technical support4. Time-span between two forecasts 4. Adaptability of user interface 4. Technical support on demand5. Oil spill risk analyses for specific geographic areas 5. Vessel information database 5. Technical support in different geographic areas6. Oil spill risk analyses for specific situations 6. Data protection systems 6. Multi-language technical support7. Hazard risk maps on specific conditions 7. Data storage systems 7. Organization of periodic workshops with experts8. Integration with other models 8. Warning systems9. Set of pollutants detected 9. Compatibility

Fig. 5. Percentage of respondents attributing a high value to model-related features.

Fig. 6. Percentage of respondents attributing a high value to software-related features.


(2) probabilistic forecasts, (3) bathymetry, (4) interactive discoveryfields, and (5) backtracking.

5. The engagement part 2 – Mobilizing the partners

The MEDESS-4MS project fosters the mobilization of stake-holders and users through the development of a multi-dimensionalsystem of relations, to take advantage of external contributions byencouraging the participation to the development of the DecisionSupport System. Such a dense system of interactions, at the same


time, aims at gaining the support of external actors in promotingthe adoption of the system within the community of oil spill “spe-cialists” and “generalists”.

Table 3 that follows describes such a system and provides anoverview of countries and organizations involved in the innova-tion process. It accounts for the “breadth” of the network (mea-sured by the number of countries and by the number of stake-holders and users) and for the “strength” of relations (measuredby the number of times organizations have been associated withthe development process and by the #Relations/ #Organizationsratio).





Fig. 7. Percentage of respondents attributing a high value to service-related features.

Fig. 8. Evaluation of extended features.


The network of organizations spans many of the countriesbordering the Mediterranean and connects a variety of institu-tional types – public and private; different geographical scope(local, national and international); different responsibilities(environment, transportation, civil protection, defense, and oth-ers); different industries (oil and gas, transportation, pollutionmanagement, and others). It involves all the key organizations inthe management of oil spills – from emergency response to pre-vention and preparedness, to recovery and restoration.

Stakeholders and users cooperate within the innovation processby performing a variety of activities. Some of them are involved in apassive way: they participate in surveys and share their opinions;describe their needs and requirements; point to value drivers, andsuggest new and additional services. Others are involved in moreactive ways, by attending meetings; by discussing the functioning of


the Decision Support System, and by introducing the system tointerested partners. Meetings ensure that stakeholders and users geta first-hand experience of the service and provide their feedbackabout it; they allow face-to-face, tighter interactions, and require astronger engagement from participants. Still others are partners ofthe project and cooperate widely to the whole development process.This involvement spans across various activities that enhance theexchange of information with partners and external actors. Amongthese activities, it is worth mentioning the participation to “seriousgames”, namely simulations to test the performance of the DecisionSupport System in real operational conditions. Overall, these activ-ities are designed to achieve the key objectives of the innovationprocess, i.e., to fine-tune the product, to facilitate the use of thesystem, to strengthen the links with key stakeholders and users, andto foster their engagement in the diffusion process.





Table 3Stakeholders’ and End Users’ involvement in the innovation process.

Country Project members Survey Meetings

Profiles Requirements Overall Model OC-UCY CEDRE CNR-INGV ITCG REMPEC #Organiz.s #Relations Rel./Org.

Albania 1 1 2 2 1.0Algeria 1 3 3 4 1.3Bosnia 1 1 1 1 1 1.0Croatia 1 4 4 5 1.3Cyprus 1 2 8 1 11 12 1.1Egypt 1 1 1 1 1.0France 1 1 4 1 2 5 9 1.8Greece 2 2 2 1 2 5 9 1.8International 1 5 3 1 2 1 6 12 19 1.6Israel 1 2 2 3 1.5Italy 2 5 5 3 1 10 6 3 17 35 2.1Malta 2 2 3 6 7 1.2Montenegro 1 1 2 1 1 1 2 7 3.5Nederlands 1 1 1 1.0Russia 1 1 1 1.0Slovenia 1 1 1 1.0Spain 2 2 3 1 1 2 5 11 2.2Syria 1 1 1 1.0Tunisia 1 3 2 6 6 1.0Turkey 1 1 2 2 1.0UK 1 1 1 1.0


6. Conclusions and future developments

The case study discussed in this paper analyzes the role playedby end users in the development and diffusion of technologicalinnovations. It points to the importance of such a role and suggestshow to harness users’ engagement in adapting the new technologyto satisfy their needs and requirements and in providing theirsupport to facilitate a widespread adoption of innovations. Thedevelopment and diffusion of innovations start with the recogni-tion of relevant users. In this case study, relevant users are the“specialists”, namely users populating the hub of the oil spillmanagement network, constantly committed to oil spill forecast-ing and management, at local, national and international levels.Then, innovations have to be fine-tuned to the requirements ofstakeholders and users. As witnessed in the development of theDecision Support System, relevant users are involved in analyzingthe drivers of value and in defining the features of this system, onthe basis of their needs and requirements. Finally, innovationshave to be promoted within the socio-economic system. As arguedin the diffusion of the Decision Support System, key users andpotential partners are mobilized to promote the innovation.

Future developments may follow a few promising paths, per-taining to technological and managerial areas. From a technolo-gical point of view, first of all, research may provide furtherimprovements to the forecasting system and perform an evalua-tion of the reliability of forecasts; second, it may focus on oil spillsfrom platforms or rigs, to reduce the risks and to mitigate theimpact of major accidents.

From a managerial point of view, this study suggests several newresearch directions. First of all, future developments may con-centrate on communication activities towards stakeholders andusers, specialists as well as generalists, to secure their engagement.Second, further research might consider the obstacles behind users’engagement in the development of a new technology, diggingdeeper in their impediments to contribute to the innovation processand identifying the contingent factors affecting such a contribution.Finally, research could also find ways to motivate stakeholders andusers to play a more active role, by capitalizing on the network ofinteractions connecting organizations and individuals.


Acknowledgments

This work was supported by the MEDESS-4MS Project(www.medess4ms.eu), co-funded by the European Regional Devel-opment Fund for the maritime risks prevention and strengthening ofmaritime safety, within the framework of the INTERREG MEDProgramme (MED Programme Project “MED 2S-MED11-01, titled:Mediterranean Decision Support System for Marine Safety(Acronym: MEDESS-4MS)” approved by the Selection Committee(SC), on 17/10/2011, Barcelona). The reports developed within theProject are the building block of this work.

References

Andersson, S., 2004. Internationalization in different industrial context. J. Bus.Ventur. 19, 851–875.

Anderson, J.C., Hakansson, H., Johanson, J., 1994. Dyadic business relationshipswithin a business network context. J. Mark. 58 (4), 1–15.

Akrich, M., Callon, M., Latour, B., 1988. À quoi tient le succès des innovations?1: l’art de l’intéressement. 2: le choix des porte-parole. Gérer et comprendre,Ann. Des. Mines 11–12 (4–17), 14–29.

Akrich, M., Callon, M., Latour, B., 2002. The key to success in innovation part II: theart of choosing good spokespersons. Int. J. Innov. Manag. 6 (2), 187–206.

Brodie, R.J., Ilic, A., Juric, B., Hollebeek, L., 2011. Customer engagement conceptualdomain, fundamental propositions, and implications for research. J. Serv. Res.14 (3), 252.

Calder, B.J., Isaac, M.S., Malthouse, E.C., 2013. Taking the Customer's Point-of-view:Engagement or Satisfaction? Report No. 13-102. Marketing Science InstituteWorking Paper Series.

Coviello, N.C., Joseph, R.M., 2012. Creating major innovations with customers:insights from small and young technology firms. J. Mark. 76 (6), 87–104.

Craig Smith, N., Drumwright, M.E., Gentile, M.C., 2010. The new marketing myopia.J. Public Policy Mark. 29 (1), 4–11.

Dwyer, F.R., Schurr, P., Oh, S., 1987. Developing buyer-seller relationships. J. Mark.51, 11–27.

Freeman, R.E., 1984. Strategic Management: A Stakeholder Approach. CambridgeUniversity Press, New York.

Gaillard J.M., 2000. Marketing et Gestion de la Recherche et Développement.Economica, Paris.

Hollebeek, L.D., 2011. Demystifying customer brand engagement: exploring theloyalty nexus. J. Mark. Manag. 27 (7–8), 785–807.

Hunt, S.D., 1994. On rethinking marketing: our discipline, our practice, ourmethods. Eur. J. Mark. 28 (3), 13–25.

Lusch, R.F., 2007. Marketing's evolving identity: defining our future. J. Public PolicyMark. 26 (2), 261–268.


http://www.medess4ms.eu

http://refhub.elsevier.com/S0967-0645(16)30156-4/sbref1








































Lüthje, C., Herstatt, C., 2004. The lead user method: an outline of empirical findingsand issues for future research. RD Manag. 34 (5), 553–568.

Moore, G.A., 1991. Crossing the Chasm, Marketing and Selling High-Tech Productsto Mainstream Customer. HarperCollins Publishers, New York.

Porter, M., 1985. Competitive Advantage - Creating and Sustaining Superior Per-formance. The Free Press, New York.

Rogers, E.M., 2003. Diffusion of Innovations, fifth ed. Free Press, New York.Rosenzweig, E.D., Roth, A.V., Dean, J.W., 2003. The influence of an integration

strategy on competitive capabilities and business performance: an exploratorystudy of consumer products manufacturers. J. Oper. Manag. 21, 437–456.

Shih, E.C., Venkatesh, A., 2004. Beyond adoption: development and application of ause-diffusion model. J. Mark. 68 (1), 59–72.

Ulrich, D., 1989. Assessing human resource effectiveness: stakeholder, utility, andrelationship approaches. Hum. Resour. Plan 12 (4), 301–315.

Urban, G.L., von Hippel, E., 1988. Lead user analyses for the development of newindustrial products. Manag. Sci. 34 (5), 569–582.

van den Bulte, C., Joshi, Y.V., 2007. New product diffusion with influential andimitators. Mark. Sci. 26 (3), 400–421.


van Doorn, J., Lemon, K.E., Mittal, V., Nab, S., Pick, D., Pirner, P., Verhoef, P.C., 2010.Customer engagement behavior: theoretical foundations and research direc-tions. J. Serv. Res. 13 (3), 253–266.

Verhoef, P., Lemon, K.N., Parasuraman, A., Roggeveen, A., Tsiros, M., Schlesinger, L.A., 2009. Customer experience creation: determinants, dynamics and man-agement strategies. J. Retail. 85, 31–41.

von Hippel, E., 1986. Lead users: a source of novel product concepts. Manag. Sci. 32(7), 791–805.

Zodiatis, G., et al., 2016. The Mediterranean Decision Support System for MarineSafety dedicated to oil slick predictions. Deep Sea Research Part II, Special Issue.

Electronic sources

http://www.medess4ms.eu/.





































http://refhub.elsevier.com/S0967-0645(16)30156-4/ir4587

http://refhub.elsevier.com/S0967-0645(16)30156-4/ir4587

http://www.medess4ms.eu/




Documents

Analysis of thedevelopment and diffusion of technological innovations in oil spill forecasting: The MEDESS-4MS case