An Integrated Framework for The Value Focused Thinking Methodology

Transcription

1 Prceedings f the 51 st Hawaii Internatinal Cnference n System Sciences 2018 An Integrated Framewrk fr The Value Fcused Thinking Methdlgy Kweku-Muata Osei-Brysn Department f Infrmatin Systems Virginia Cmmnwealth University, U.S.A KMOsei@VCU.Edu Abstract: In this paper we presented an integrated framewrk fr the Value Fcused Thinking (VFT) methdlgy that attempts t address issues that have nt been adequately addressed. This framewrk prvides several benefits including: the elicitatin and high quality definitin f bjectives that incrprates rganizatinal-riented & dmainriented cncerns and knwledge, and the autmatic generatin f the alternate slutins that best satisfy the bjectives, cnstraints and preference values. The prpsed framewrk culd cntribute t a mre effective applicatin f the VFT methdlgy. 1. INTRODUCTION The Value-Fcused Thinking (VFT) methdlgy (Keeney [1] [2]), prvides guidance n the frmulatin f bjectives, an indispensable task in any decisin making situatin. VFT has been applied acrss a wide variety f dmains such as prject management (Barclay & Osei-Brysn [3]), turism management (Kajanus et al. [4] ),systems engineering (Bylan et al., [ 5]), ERP Systems (May,Dhilln & Caldeira [6]), IS Security (Maitland, Barclay & Osei- Brysn [7], Dhilln & Trkzadeh [8]). Within the cntext f the VFT methdlgy (e.g. Barclay [9]) bjectives are classified as being either a fundamental bjective (FO) r a means-bjective (MO), where each MO is an bjective that is required in rder t directly achieve its parent FO r anther MO. VFT can dne in a tp-dwn r bttm manner, with ur fcus in this paper being n the frmer. In a tpdwn apprach Means Objectives (MO) are btained frm fundamental bjectives (FO), by determining fr each FO all the immediate lwer level things that must be dne satisfactrily (i.e. MO) in rder t achieve the given FO. Lwer level MOs can be btained fr next higher level MOs in a similar manner. The result is a netwrk f bjectives with the FOs at the rt level and a subset f the MOs at the leaf level. Each leaf level MO can be cnsidered t be equivalent t an actinable gal. 1. Frame the Decisin Situatin a. Define the Decisin Cntext: This is framed by the assciated Administrative, Plitical & Scial structures b. Identify the Objectives c. Structure the Objectives int a Means- Ends Netwrk d. Specify Attributes 2. Preference Elicitatin 3. Create Alternatives 4. Recmmended Decisin 5. Sensitivity Analysis In this paper we present a new integrated framewrk fr the VFT prcess that will address the fllwing issues: Ø Decisin Cntext: Studies invlving the applicatin f the VFT methdlgy culd be cnsidered t fall int categries: a) thse that attempt t identify Fundamental Objectives (FOs) & Means Objectives (MOs) relevant t a given dmain within specific situatin rganizatin (e.g. Barclay & Osei-Brysn [3]); and b) thse that thse that attempt t identify FOs & MOs that are generally relevant t a given dmain (e.g. Dhilln & Trkzadeh [8]). A fundamental cncern with the latter apprach is that VFT is t be applied within a particular decisin cntext that is determined by relevant administrative, scial, cultural & plitical structures, and decisin styles, and as such the decisin cntexts fr a given dmain (e.g. security) culd vary acrss rganizatins. Ø Types f Relatinships between Objectives: There are several types f relatinships that culd exist between bjectives including: Parent-Child (PC) URI: ISBN: (CC BY-NC-ND 4.0) Page 1473

2 Ø Ø Intrinsic Cnflict (IC): The bjectives cnflict by their very nature (i.e. the relevant desired directins f the given pair f bjectives cannt be simultaneusly achieved, nt because they cmpete fr the same resurces but because they instrinsically cnflicting. An example f this is the intrinsic between the Cnfidentiality & Availability bjectives f a security plan: having maximum Cnfidentiality results in minimum Availability, and vice versa. Resurce Cnflict (RC): The given pair f Objectives utilize & thus cmpete fr ne r mre resurces, and because f this fact the relevant desired directins f the given pair f bjectives cannt be simultaneusly achieved. The traditinal VFT prcess explicitly fcuses n PC relatinship types nly, althugh bth IC & RC are relevant t the Create Alternatives step f the VFT methdlgy. The apprach presented in this paper will fcus n all relatinship types. Quality f the Descriptin f the Objectives: It is imprtant that the bjectives have imprtant quality prperties including Relevance, Cmpleteness (i.e. fr a given nn-leaf bjective, all f its relevant child Means Objectives must be specified), Nn-Redundancy (i.e. N tw bjectives in the same tier shuld verlap), Specificity (i.e. must lead t an bservable actin, behavir r achievement) The traditinal VFT prcess des nt explicitly fcus n assessing all relevant quality dimensins. Need t Create Values-based Alternatives: Keeney [2] nted that The first alternatives that cme t mind are the bvius nes Truly different alternatives remain hidden in anther part f the mind, unreachable by mere tweaking Fcusing n the values that shuld be guiding the decisin situatin remves the anchr n the narrwly defined alternatives the means bjectives are als meaningful grund t stimulate thinking abut the bjectives. We adpt these insights t design a methd fr the autmatic generatin f the alternatives that factrs bth the relevant preference values and cnstraints. 2. OVERVIEW ON SOME SUPPORTING FRAMEWORKS In this sectin we present verviews n sme f the supprting framewrks that culd be utilized. 2.1 The S.M.A.R.T Framewrk: Several framewrks have been prpsed fr evaluating the quality f a business bjective including the SMART framewrk (Dran [10]) which suggested the fllwing set f criteria: Specific: It must lead t an bservable actin, behavir r achievement that can be measured Measurable: Clearly defined metrics shuld be available fr measuring the achievement f the bjective. This is particularly relevant fr the MOs Achievable: It must be achievable within the cnstraints f the available resurces, knwledge & time. Relevant: Must be relevant t the brader gals f the rganizatin Time-bund: there shuld be specific deadlines fr the achievement f the bjective. This is particularly relevant fr the MOs. A review f previus VFT papers shws that ften the MOs are nt expressed in a manner that can be cnsidered t be Time-bund. Further the Achievability criteria is ften nt cnsidered particularly with respect t the Intrinsic Cnflict (IC) and Resurce Cnflict (RC) types f cnstraints. 2.2 Sme Relevant Organizatinal Issues The reader may recall that the Decisin Cntext is framed by the assciated Administrative, Plitical & Scial structures. Thus there are several types f rganizatinal issues that have t be accmmdated in the definitin f the bjectives. We will fcus n a few f these belw Overview n the Organizatinal Types: Curtney [11] presented a set f rganizatinal types, and crrespnding rganizatinal decisin-making style. It seems reasnable t expect that the rganizatinal decisin-making style wuld impact n the feasibility and definitin f the MOs. Page 1474

3 Organizatinal Decisin-Making Style Leibniz Lcke Kant Hegel Singer Frmal Open Open Cnflictual Telelgical Analytical Cmmunicative Analytical Cperative Bureaucratic Cnsensual Ethical Overview n Individual Decisin Styles: Rwe & Bulgarides [12] identified fur majr categries f individual decisin styles. Martinsns & Davisn [13] bserved that in different cultures, different individual decisin styles are dminant. It seems reasnable t expect that in sme settings the individual decisin-making style wuld impact n the feasibility and definitin f the MOs. Style Analytical Behaviral Cnceptual Directive Descriptin Achievement riented withut the need fr external rewards; make decisins slwly because rientatin t examine the situatin thrughly and cnsider many alternatives systematically Strng peple rientatin, driven primarily by a need fr affiliatin; typically receptive t suggestins, willing t cmprmise, and prefer lse cntrls Achievement & peple riented with the need fr external rewards; make decisins slwly because rientatin t examine the situatin thrughly and cnsider many alternatives systematically Results and pwer riented but prefer t cnsider a limited number f alternatives that they cnsider Overview n the Cultural Dimensins: Hfstede [14] defined a set f cultural dimensins that culd impact the behavirs f rganizatinal actrs that are utlined belw. The characteristics f a given natinal culture may mean that sme Means Objectives are infeasible in that cntext. It is therefre imprtant that cultural issues be taken int cnsideratin. Dimensin Pwer Distance Individualism- Cllectivism Masculinity- Femininity Uncertainty Avidance Descriptin Reflects the extent t which the members in a sciety accept the unequal distributin f pwer Reflects the degree t which peple are able and prefer t achieve an identity and status n their wn rather than thrugh grup memberships Reflects the degree t which assertiveness and achievement are valued ver nurturing and affiliatin Reflects discmfrt with ambiguity and incmplete infrmatin Overview n Organizatinal Perspectives: Kaplan & Nrtn ([15] [16]) presented the Balanced Screcard (BSC) Mdel that invlves 4 perspectives presented in the table belw. An explratin f these perspectives culd lead t the discvery f imprtant rganizatinal values and bjectives. Perspective Custmer Internal Business Financial Innvatin & Learning Descriptin Hw d the custmers see the rganisatin? What must the rganisatin excel at? Hw des the rganisatin lk t the sharehlders? Hw can the rganisatin cntinue t imprve and create value? Page 1475

4 2.3 Prbing Questins The imprtance f prbing questins in the elicitatin prcess has been recgnized by previus VFT researchers. Fr example Step 1 f the research apprach f Dhilln & Trkzadeh [8] invlves using prbes t develp in depth understanding f the decisin prblem. In this subsectin we list sme relevant prbing questins; these questins are influenced by the material presented in subsectins 2.1 & Frame the Decisin Situatin a. Define the Decisin Cntext: This is framed by the assciated Administrative, Plitical & Scial structures i. What is the rganizatin type f yur rganizatin in the sense f Curtney [11]? ii. What is the nature f the prblem & its Envirnment? Wh are the majr relevant external players (i.e. Custmers, Vendrs, Cmpetitrs, Regulatrs)? What are the Ecnmic, Technical, Time & ther resurce factrs that appear t be relevant? iii. Wh are the decisin-makers (DMs) and what are their individual decisin styles? iv. What are the DM s values? v. Which grups wuld be impacted by the decisin(s)? Which grups wuld have t implement the decisin(s)? Which grups (internal r external) culd cnstrain decisin ptins? vi. What are sme knwn decisin alternatives? b. Identify the Objectives: This requires that in each case an Object is identified as well as the Directin f Preference. Questins that culd guide the identificatin include: i. What are the ultimate bjectives? ii. What are the perceived Best Practices fr the given decisin prblem dmain? What are the previusly identified Objectives fr the given decisin prblem dmain? iii. What are sme cncerns frm a Financial iv. What are sme cncerns frm an External Stakehlder WHO are yur Custmers & WHAT wuld they be cncerned abut? What wuld yur Vendrs be cncerned abut? What wuld yur Cmpetitrs be cncerned abut? What wuld yur Regulatrs be cncerned abut? What wuld yur Sharehlders be cncerned abut? v. What are sme cncerns frm an Internal Stakehlder What are sme cncerns frm a Cultural What are sme cncerns frm a Decisin Style What are sme cncerns frm a Ethical What are sme cncerns frm a Health & Safety vi. What are sme cncerns frm a Learning & Innvatin vii. What are sme cncerns frm a Scheduling viii. What are sme cncerns frm a Legal ix. What are sme cncerns frm a Technical/Technlgical 3. DESCRIPTION OF THE INTEGRATED EXTENDED VFT METHODOLOGY Belw we present a descriptin f the prpsed integrated framewrk fr the VFT methdlgy. The reader shuld nte that the first tw phases (i.e. BU & DU) present prbes that culd be used t develp an in-depth understanding f the decisin prblem. Page 1476

5 3. 1 Business Understanding (BU): This phase is cncerned with expsing & recrding the rganizatinal factrs that shuld be included in the framing f the Decisin Cntext. Relevant prbing questins include: What are the ultimate bjectives fr the given decisin prblem dmain? What are the previusly identified Objectives fr the given decisin prblem dmain? What are the significant cncerns frm a Financial What are the significant cncerns frm an External Stakehlder What are the significant cncerns frm an Internal Stakehlder What are the significant cncerns frm a Learning & Innvatin What are the significant cncerns frm a Scheduling What are the significant cncerns frm a Legal Steps in this phase wuld include: 1. Obtain & Review Organizatin Missin & Visin statements, Organizatin Chart / Organizatinal Ontlgy, Main Prducts/Services 2. Identify relevant Internal & External Stakehlders 3. Determine the Main Decisin Styles f relevant Internal Stakehlders 4. Use the relevant prmpting questins t identify the cncerns frm the 6 rganizatinal perspectives listed abve. Recrd these cncerns 3.2 Dmain Understanding (DU): This phase is cncerned with expsing & recrding the dmain issues that shuld be included in the framing f the Decisin Cntext. Relevant prbing questins include: What are the perceived Cncepts fr the dmain f the given decisin prblem? What are the previusly identified Objectives fr the given decisin prblem dmain? What are the perceived Best Practices fr the given decisin prblem dmain? What are sme cncerns frm a Learning & Innvatin What are sme cncerns frm a Legal What are sme cncerns frm a Technical/Technlgical Steps in this phase wuld include: 1. Review relevant dmain knwledge bases. 2. Use the relevant prmpting questins t identify relevant dmain-riented Cncepts, Best Practices, Fundamental & Means Objectives, and cncerns frm the 4 perspectives listed abve. Recrd this infrmatin. 3.3 Mdeling Objectives (MD): This phase has 3 sub-phases as described belw Initial Identificatin f Objectives 1. Use the recrded infrmatin that resulted frm the Business Understanding & Dmain Understanding phases t identify Objectives that meet the Relevance criteria. 2. Refine definitin f each Objective s that it satisfies the Specificity prperty Classificatin & Refinement f Objectives 1. Classify each Objective in the current set f Objectives as being a FO r a MO, and identify the assciated set f Parent-Child (PC) relatinships. 2. Fr each FO, determine if its current set f supprting child MOs is sufficient fr the given FO t satisfy the Cmpleteness prperty. If the Cmpleteness prperty is nt satisfied fr a given FO then identify the remaining supprting child MOs s that this prperty is satisfied. Update the assciated set f Parent-Child (PC) relatinships. 3. Fr each MO that is a parent f ther MOs determine if its current set f supprting child MOs is sufficient fr the given MO t satisfy the Cmpleteness prperty. If the Cmpleteness prperty is nt satisfied fr a given FO then identify remaining supprting child MOs s that this prperty is satisfied. Update the assciated set f Parent-Child (PC) relatinships. 4. Fr each MO use the Why-Is-It-Imprtant (WITI) test t determine if it has any the ther bjective (i.e. anther MO r a FO) is als its parent. Update the set f Parent-Child (PC) relatinships. 5. Review the current set f MOs in rder t identify the leaf-level MOs. 6. Fr each leaf-level MO, refine its definitin s that it satisfies the Measurability, Achievability and Time-bundedness prperties. Page 1477

6 It shuld be nte that after the cmpletin f this subphase that the Cmpleteness prperty and the 5 SMART prperties wuld have been satisfied Identificatin f Achievement Prcesses (APs) 1. Define an rdered discrete set f qualitative perfrmance levels will be specified (e.g. High, Medium, Lw). 2. Fr each leaf-level MO: a. Use the Gal Questin Metric (e.g. Basili, Caldiera, & Rmbach [17]) methd t identify relevant perfrmance measures (i.e. attributes); b. Fr each f its crrespnding qualitative perfrmance level l, identify the cmbinatins f attribute levels that are assciated with level l. Let Η jl be the crrespnding set f attribute level cmbinatins; c. Identify a set f Achievement Prcesses that culd be used realize the varius perfrmance levels f the given leaflevel MO. d. Estimate the cst and requirements f depletable resurce necessary fr a given Achievement Prcess t realize each perfrmance level f the MO. e. Identify any additinal cnstraints (e.g. Legal, Technlgical, Scheduling) based n the Cncerns/Issues identified in BU & DU phases that relate t the achievement f relevant perfrmance levels. It shuld be nted that while a MO describes WHAT is desired, a crrespnding Achievement Prcess (AP) wuld describe HOW the given WHAT culd be achieved. Descriptin f an AP includes its methd as well as a descriptin f the resurces that are required t achieve the relevant perfrmance levels f the MO. It shuld be nted that resurce requirements that are estimated in this sub-phase culd be used fr the identificatin f Resurce Cnflict (RC) relatinships. Further the fact that at this stage each FO & MO satisfies the Specificity prperty then relevant infrmatin is als available t identify any Intrinsic Cnflict (IC) relatinship between perfrmance levels f pairs f Objectives. 3.4 Elicit Preference Infrmatin 1. Use a pairwise cmparisns apprach such as that used in the AHP t determine, w i, the relative imprtance f each FO i. 2. Fr each FO i, use a pairwise cmparisns apprach t determine the relative value v ik f each pssible scre level k. 3.5 Generate & Evaluate Alternatives: This phase has tw sub-phases. The first sub-phase fcuses n the frmulatin f a mathematical prgramming prblem (MPP) that wuld be used fr generating the alternatives that are reflective f the preference values and als relevant cnstraints. This MPP culd als be use t d What-If and sensitivity analyses. The secnd sub-phase utlines the prcedure fr frmulating & slving the MPP t generate and evaluate alternate slutins, including near ptimal nes Mathematical Prgramming Frmulatin Ø I is the set f Objectives; I FO is the subset f Fundamental Objectives (FO); I MO is the subset f Means Objectives (MO); I = I FO I MO ; I FO I MO =. Ø v ik is the value assciated with FO i being achieved at level k K i. Ø x ik is a binary variable such that x ik = 1 indicates that Objective i has been achieved at level k ; and x ik = 0 therwise. Parent-Child Cnstraints n Achievement f Perfrmance Levels: Ø M ik is the set f cmbinatins f MOs each at a specified perfrmance level l, such that each cmbinatin in M ik wuld result Objective i being achieved at perfrmance level k. Fr each m M ik, J ikm is a set f MOs, each a child f Objective i and each at a perfrmance level that taken tgether wuld result in Objective i being achieved at level k. z ikm is a binary variable such that z ikm = 1 indicates that each MO j in J ikm is at the relevant perfrmance level l; and z ikm = 0 therwise. Page 1478

7 1a: z ikm x jl 0 m M ik, (j,l) J ikm 1b: Σ (j,l) Jikm x jl - z ikm ( J ikm - 1) m M ik Ø Objective i is achieved at level k nly if at least ne cmbinatin in M ik is realized: 2: x ik - Σ m Mik z ikm 0 i I, k K i Ø Each bjective i achieves exactly ne f its allwable levels k K i 3: Σ k Ki x ik = 1 i I Resurce Cnflicts: Ø q rjl is the minimum amunt f depletable resurce r that is required in rder fr MO j t be achieved at level l, and q r be the ttal available amunt f resurce r : (4) Σ j IMO Σ l Ki q rjl x jl q r r R Intrinsic Cnflicts: Ø P is the set f pairs f Objectives, (i 1, i 2 ) that have Intrinsic Cnflicts where i 1 I & i 2 I such that if i 1 I achieves level k 1 then i 2 I cannt achieve level k 2. (5) x i1,k1 + x i2,k2 1 (i 1,k 1, i 2, k 2 ) P Integer Prgramming Prblem (MPP) t Generate Alternatives: IP GenAlt : Max {Σ i IFO Σ k Ki w i v ik x ik (1) (5), & binary restrictin n all variables} Prcedure fr Generating Alternatives 1. Frmulate & Slve prblem P GenAlt. 2. Given the initial ptimal slutin t prblem P GenAlt, generate ther alternate ptimal slutins if they exist. 3. Use What-If and/r Sensitivity Analysis t generate ther alternate thugh near ptimal slutins t prblem P GenAlt. 4. ILLUSTRATIVE EXAMPLE In this sectin we present an illustrative example that applies the prcedure fr generating alternatives that satisfy the three types f cnstraints. Figure 1 displays the Means-Ends Objective Netwrk (a hierarchy in this case) fr an infrmatin systems security. Lw (1)) fr each Objective. Table 1 displays the cnstraints that represent these facts. Rather than use x and y fr the variable names we have the variable that represents each Means Objective (MO) level begin with M, and the variable that represents each Fundamental Objective (FO) level begin with F where each variable is a 0/1 integer variable. Figure 1: Means-Ends Objectives Netwrk MO_11 FO_1: Cn0identi ality Table 1: Select One Perfrmance Level Cnstraint Means MO_11 M111 + M112 + M113 = 1 MO_12 M121 + M122 + M123 = 1 MO_21 M211 + M212 + M213 = 1 MO_22 M221 + M222 + M223 = 1 MO_31 M311 + M312 + M313 = 1 MO_32 M321 + M322 + M323 = 1 Fundament al MO_12 MO_21 Values FO_2: Integrity MO_22 MO_31 FO_3: Availabilit y MO_32 FO_1 F11 + F12 + F13 = 1 FO_2 F21 + F22 + F23 = 1 FO_3 F31 + F32 + F33 = 1 Tables 2 4b displays the varius ther types f cnstraints: Parent-Child Cnstraints n Achievement f Perfrmance Levels (Table2), Intrinsic Cnflict (Table3), and a financial Resurce Cnflict (Tables 4a & 4b). Table 5a displays the Weight fr each Fundamental Objective (FO) and the Value assciated with achieving each perfrmance level f each FO. The value f the highest level (i.e.. Level 3) f each Fundamental Objective is set t 100, with the value f its lwer levels be relative t the value f the highest level. Methds such as the Analytic Hierarchy Prcess (e.g. Saaty [18], Brysn [19] culd be used t bth derive the relative weight f each FO as well fr each FO the relative value f its lwer perfrmance levels with respect t its highest perfrmance level. In the Table 5b, the cefficient f each variable is its weighted Value. Fr each Objective, exactly 1 Perfrmance Level can be achieved. Further there are three pssible perfrmance levels (i.e. High (3), Medium (2), and Page 1479

8 Table 2: Parent-Child Cnstraints If MO_11 & MO_12 M113 + M123 F13 <= 1 are bth at Level 3 then F13 M113 <= 0 FO_1 is at Level 3; F13 M123 <= 0 If MO_11 & MO_12 are bth at Level 1 then FO_1 is at Level 1; If MO_21 & MO_22 are bth at Level 3 then FO_2 is at Level 3; If MO_21 & MO_22 are bth at Level 1 then FO_2 is at Level 1; If MO_31 & MO_32 are bth at Level 3 then FO_3 is at Level 3; If MO_31 & MO_32 are bth at Level 1 then FO_3 is at Level 1; M111 + M121 F11 <= 1 F11 M111 <= 0 F11 M121 <= 0 M213 + M223 F23 <= 1 F23 M213 <= 0 F23 M223 <= 0 M211 + M221 F21 <= 1 F21 M211 <= 0 F21 M221 <= 0 M313 + M323 F33 <= 1 F33 M313 <= 0 F33 M323 <= 0 M311 + M321 F31 <= 1 F31 M311 <= 0 F31 M321 <= 0 Table 3: Intrinsic Cnflict Cnstraint Cnfidentiality (FO_1) & F13 + F33 <= 1 Availability (FO_3) cannt bth be at Level 3 Table 4a: Objective Level Achievement Csts Fundamental Means Level Cst Cnfidentiality MO_ (C) MO_ Integrity (I) Availability (A) 1 55 MO_ MO_ MO_ MO_ Table 4b: Financial Resurce Cnstraint 110M M M M M M M M M M M M M M M M M M321 Table 5a: Weights & Achievement Level Values Fundamental Objective Weight Level Value Cnfidentiality (C) Integrity (I) Availability (A) Table 5b: Objective Functin f IP Prblem 37.00F F F F F F F F F31 In Table 6 we display the results f slving the IP prblem under 3 scenaris: Nne (i.e. n additinal cnstraint), Cnfidentiality must be at its tp perfrmance level (i.e. Set FO_1 t Level 3), and Integrity must be at its tp perfrmance level (i.e. Set FO_2 t Level 3). Fr scenari, the perfrmance levels f the FOs and MOs are prvided. Since fr each MO its crrespnding Achievement Prcess wuld have previusly identified then results generated by the Prcedure fr Generating Alternatives culd be used t identify the perfrmance levels f the relevant Achievement Prcess that crrespnds t the given set f MOs perfrmance levels. 5. CONCLUSION In this paper we presented an integrated framewrk fr the Value Fcused Thinking methdlgy that attempts t address significant issues that have nt been adequately addressed. This framewrk prvides several benefits including: the elicitatin and high quality definitin Objectives that accmmdate rganizatinal-riented & dmain-riented cncerns Page 1480

9 and knwledge; and the autmatic generatin f the Alternate slutins that best satisfies the three types f relatinship cnstraints and the preference values. It als ffers the ptin f sensitivity and What-If analysis. This new VFT framewrk culd cntribute t a mre effective applicatin f the VFT methdlgy that is being increasingly used in a variety f situatins (e.g. [3], [4], [5], [6], [7], [8], [20]). Table 6: Descriptin f the Generated Alternatives Restrictin Value Fundamental Means Obj Lvl Obj Lvl Nne FO_1 2 MO_11 2 MO_12 1 FO_2 2 MO_21 1 MO_22 3 FO_3 3 MO_31 3 MO_32 3 Set FO_1 t Level 3 Set FO_2 t Level 3 REFERENCES FO_1 3 MO_11 3 MO_12 3 FO_2 2 MO_21 3 MO_22 1 FO_3 2 MO_31 2 MO_ FO_1 1 MO_11 1 MO_12 1 FO_2 3 MO_21 3 MO_22 3 FO_3 3 MO_31 3 MO_ Keeney, R. L. (1992). Value-Fcused Thinking: A Path t Creative Decisin Making: Harvard University Press. 2. Keeney, R. L. (1996) Value-Fcused Thinking: Identifying Decisin Opprtunities and Creating Alternatives, Eurpean Jurnal f Operatinal Research 92, Barclay, C. & Osei-Brysn, K.-M. (2010) "Prject Perfrmance Develpment Framewrk: An Apprach fr Develping Perfrmance Criteria & Measures fr Infrmatin Systems (IS) Prjects", Internatinal Jurnal f Prductin Ecnmics 124:1, Kajanus, M., J. Kangas, & Kurtilla, M. (2004) "The Use f Value Fcused Thinking and the A WOT Hybrid Methd in Turism Management", Turism Management 25:4, Bylan, G. L., E. S. Tllefsn, Kwinn, M., & Guckert, R. (2006) "Using Value-Fcused Thinking t Select a Simulatin Tl fr the Acquisitin f Infantry Sldier Systems", Systems Engineering 9: May, J., Dhilln, G., & Caldeira, M. (2013). Defining value-based bjectives fr ERP systems planning. Decisin Supprt Systems, 55(1), Barrett-Maitland, N., Barclay, C., & Osei-Brysn, K. M. (2016). Security in Scial Netwrking Services: A Value-Fcused Thinking Explratin in Understanding Users Privacy and Security Cncerns. Infrmatin Technlgy fr Develpment, 22(3), Dhilln, G. & Trkzadeh, G. (2006) Value-fcused assessment f infrmatin system security in rganizatins, Infrmatin Systems Jurnal 16:3, Barclay, C. (2014) Overview f the Value-fcused Thinking methdlgy. In Advances in Research Methds fr Infrmatin Systems Research (pp ). Springer US. 10. Dran, G. (1981) "There s a S.M.A.R.T. Way t Write Management Gals and Objectives", Management Review 70:1, Curtney, J. (2001) Decisin making and knwledge management in inquiring rganizatins: tward a new decisin-making paradigm fr DSS, Decisin Supprt Systems 31, Rwe, A. J., & Bulgarides, J. D. (1983) Decisin Styles - A Perspective, Leadership & Organizatin Develpment Jurnal, 4(4), Martinsns, M. & Davisn, R. (2007) Strategic decisin making and supprt systems: Cmparing American, Japanese and Chinese management, Decisin Supprt Systems 43, Hfstede, G. (1980) Culture's Cnsequences: Internatinal Differences in Wrk-Related Values, Sage Publicatins, Beverly Hills, CA. 15. Kaplan, R. & Nrtn, D. (1992) "The Balanced Screcard: Measures That Drive Perfrmance", Harvard Business Review 70:1, Kaplan, R. S., & Nrtn, D. P. (2001). The strategyfcused rganizatin: Hw balanced screcard cmpanies thrive in the new business envirnment. Harvard Business Press. 17. Basili, V., Caldiera, G., & Rmbach, H (1994) The Gal Questin Metric Apprach, Encyclpedia f Sftware Engineering. 18. Brysn, N. (1996) "Grup Decisin-Making and the Analytic Hierarchy Prcess: Explring the Cnsensus- Relevant Infrmatin Cntent", Cmputers & Operatins Research 23, Saaty, T. (1980) The Analytic Hierarchy Prcess: Planning, Pririty Setting, Resurce Allcatin, McGraw-Hill, NY. 20. Osei-Brysn, K.-M. & Ngwenyama, O. (2014) Advances in Research Methds fr Infrmatin Systems Research: Data Mining, Data Envelpment Analysis, Value Fcused Thinking. Springer Series, New Yrk. Page 1481